Audio

🎙️ VibeVoice now on Hugging Face – Microsoft’s open-source 8B speech model gained a Transformers-compatible build on Hugging Face, enabling direct inference without custom setup. The model handles 60-minute audio in a single pass with speaker diarization and timestamps across 51 languages.

Autonomous Agents

🧠 Ineffable Intelligence bets on pure RL – David Silver, co-creator of AlphaGo, launched Ineffable Intelligence to build a superlearner driven entirely by reinforcement learning from environment experience, without relying on human-generated training data, aiming at what the company calls first contact with superintelligence.

⚡ Stripe Projects for agent provisioning – Stripe launched a developer preview letting developers and agents provision hosting, databases, auth, analytics, and other services from the CLI. Credentials sync back to the local environment automatically, and billing consolidates across all connected providers.

🗺️ What to learn in AI agents – A practitioner’s guide on durable vs transient knowledge in the current agent landscape, arguing that framework API mastery compounds poorly while systems thinking, debugging intuition, and taste for boring architectural choices remain the skills worth building.

Biotech, Health, and Chemistry

🔬 TxPert reaches Nature Biotechnology – A knowledge-graph approach to predicting transcriptomic perturbation effects achieved performance close to split-half experimental reproducibility for single unseen perturbations, and outperformed existing methods by 8 to 25% on double perturbations and cross-cell-line predictions. The first model in this class to move from preprint to peer-reviewed publication.

🌊 Virtual cell research at ICLR 2026 – Reflections from ICLR 2026 in Rio mapped the fragmentation in the virtual cell field: more models and investment than ever, but no shared evaluation infrastructure or common definitions. The piece argued for disease-specific models over universal cell simulators, with Eva from Scienta Lab cited as a positive example.

🧪 Orthrus RNA isoform foundation model – A Mamba-based mature RNA foundation model pretrained via contrastive learning on splicing isoforms and orthologous transcripts across 400+ mammalian species, published in Nature Methods. It outperforms genomic foundation models on mRNA property prediction with substantially less fine-tuning data. The first author co-founded blank.bio, applying the same approach to clinical precision medicine.

Image, Video & 3D

🔮 Power Foam: ray tracing meets rasterization – A differentiable 3D representation combining foam-based ray tracing efficiency with 3DGS-level rasterization performance. Uses bounded power diagrams with controllable cell extents to achieve consistent high-frame-rate output under both rendering paradigms from the same scene representation.

🎬 Vista4D video reshooting via 4D – A video reshooting framework from Eyeline Labs (powered by Netflix) that grounds input video and target cameras in a 4D point cloud, enabling novel-viewpoint synthesis while preserving scene dynamics. Supports camera trajectory changes, 4D scene recomposition, and dynamic scene expansion.

Cyber

🔴 CVE-2026-31431: critical Linux LPE – A 732-byte Python script roots every Linux distribution shipped since 2017 (!) by chaining a logic bug in authencesn through AF_ALG and splice() into a page-cache write. Requires only an unprivileged local user account, no race window, and no per-distro kernel offset.

• The exploit works unmodified on Ubuntu, Amazon Linux, RHEL, and SUSE without any per-distribution tuning, and is expected to behave identically on Debian, Arch, Fedora, and other distros running affected kernels.

• Kubernetes and multi-tenant environments carry the highest risk, as the shared page cache allows a pod with the right primitives to cross tenant boundaries and compromise the entire node.

• Priority patching applies to multi-tenant Linux hosts, CI runners executing untrusted PR code, container clusters, and any environment running tenant-supplied notebooks, agents, or serverless functions.

Infrastructure

🏥 Scaleway wins France’s Health Data Hub – Following a rigorous 350-criteria selection process, Scaleway was designated to host France’s Health Data Hub including a copy of the national health database. The selection turned on HDS certification and a credible roadmap toward SecNumCloud qualification.

• Community take w/ Robert Hommes: “The Dutch government and central bank also announced Stackit sovereign cloud pilots. And there’s Euro-Office, an EU-driven initiative for a sovereign, Microsoft-compatible office suite to replace US alternatives.”

💥 AI agent wipes production database – A coding agent running on Cursor + Opus 4.6 used a Railway API token created for domain operations to delete both a production database and all volume-level backups in 9 seconds. Railway stores volume backups within the volume itself, and tokens provisioned via the CLI carry undisclosed blanket authority over the entire GraphQL API, including destructive volume deletion.

Language Models

📉 DeepSeek slashes V4-Pro API prices – V4-Pro input token prices dropped 75% in a promotional offer running until May 5, with the model already undercutting GPT-5.5, Claude Opus 4.7, and Gemini 3.1 Pro at full price. Cache hit prices were simultaneously cut to one-tenth across the entire API suite, targeting agentic applications with repetitive inputs.

Programming

🎼 Symphony: open spec for Codex orchestration – OpenAI published Symphony, a written spec that turns issue trackers like Linear into always-on agent orchestrators, assigning one Codex agent per open task. Internal use yielded a 500% increase in landed pull requests on some teams.

🖥️ Zed editor hits version 1.0 – The Rust-based collaborative code editor shipped its first stable release.

🤖 Laguna XS.2 for agentic coding – Poolside’s first public model is a 33B parameter MoE with only 3B activated per token, designed for agentic coding and long-horizon tasks on local hardware. Scores 68.2% on SWE-bench Verified and runs on a Mac with 36GB RAM via Ollama under Apache 2.0.

💬 Karpathy on LLM new horizons – A fireside chat at Sequoia Ascent 2026 argued that LLMs enable three genuinely new capability categories beyond productivity gains: apps fully reducible to LLM inputs and outputs, plain-language install instructions replacing bash scripts, and unstructured knowledge bases previously impossible with classical code.

🧱 Better-T-Stack interactive stack builder – An interactive web UI for composing a TypeScript full-stack from modular picks across frontend, backend, runtime, database, auth, and native layers, generating a ready-to-run CLI command on the fly.

🎥 AI coding works, that’s the problem – A YouTube essay mapped the quantitative impact of AI on software development in web and game dev, then examined the economic and career consequences, arguing that accelerating output does not automatically preserve demand for individual developers.

Contributors This Week

Félix Raimundo, Ihab Bendidi, Aly Moursy, Robert Hommes, Youssef Tharwat, Quentin Dubois, Christophe Lesur, Louis Choquel, Timothy Lindblom, Amine Saboni, Antoine Millet, Gabriel Duciel, Gabriel Olympie, Hani Chalouati, Hugo Hernandez, Karim Matrah, Louis Manhes, Paul Masurel, Stan Girard

Events

🇺🇸 AgentCon Silicon Valley in Mountain View (May 4) – Free conference for developers building with AI agents at the Computer History Museum. Sacha Morard is speaking on token optimization for coding agents, covering techniques, frameworks, and live session data from Edgee.

🇳🇱 Amsterdam Tech Week (June 16–19) – The second edition of Amsterdam Tech Week returns across four days with startup events ranging from technical workshops to networking sessions, organized by local startups and VCs.

Audio

🎙 Headroom expands to voice – Headroom, the open source context compression layer for LLMs that saved 100B tokens in 25 days, has launched kompress-voice, a new model for voice applications. It integrates with ElevenLabs and Cartesia, runs locally, claims significant token savings, and does not collect user data. The team is seeking early design partners. 👉 Tejas Chopra.

Autonomous Agents

🎥 Skills, MCP, and code mode demystified – A 20-minute must-watch talk at the MCP Dev Summit with Nikolay Rodionov from Alpic breaking down the three paradigms: Skills are context-efficient reusable prompts loaded progressively, MCP provides structured cross-platform tool access, and Code Mode executes scripts in a sandbox to avoid context bloat.

🦀 Microsoft Rust guidelines for agents – Microsoft’s Pragmatic Rust Guidelines, covering idiomatic API design, safety, documentation, and testing, are available as a single agent-ready text file. Dropping it into a coding agent skill showed measurable quality improvements in generated Rust code. https://microsoft.github.io/rust-guidelines/agents/all.txt

📦 Multi-language agent skills pack – Youssef Tharwat’s set of agent skills, inspired by Microsoft’s Rust guidelines, covers lint rules, design guidelines, and idiomatic patterns for Rust, Python, and TypeScript. It draws from Microsoft guides, Google style guides, Ruff, Oxlint, and GoF patterns. Works with Claude Code, Codex, Cursor, and 30+ other agents via npx skills add.

Image, Video & 3D

🍌 Vision Banana unifies vision and generation – Google DeepMind’s Vision Banana instruction-tunes an image generator to handle segmentation, depth estimation, surface normals, and other vision tasks by treating them as image generation problems, beating specialist models zero-shot. Paper is here.

• Reframes all 2D and 3D perception tasks as RGB image generation, producing outputs like segmentation masks or depth maps directly rather than through separate decoder heads.

• Beats Segment Anything Model 3 on segmentation tasks and the Depth Anything series on metric depth estimation without any task-specific training or architecture changes.

• Achieves these results via lightweight instruction-tuning on top of Nano Banana Pro (NBP) without sacrificing the base model’s image generation capabilities.

🔥 ChatGPT Images 2.0 released – OpenAI released a new image generation model for ChatGPT with significantly improved text rendering, multilingual support, and advanced visual reasoning. Community testing confirmed sharper text output, though the model dropped alpha layer support compared to gpt-image-1.

🗺 LingBot-Map autoregressive 3D reconstruction – A purely autoregressive 3D foundation model achieving approximately 20 FPS at 518x378 resolution over sequences exceeding 10,000 frames. Builds geometric context attention with long-context modeling while maintaining a compact streaming state, with no post-processing or optimization passes required.

🎭 Image models for sensitive content – Community explored which image generation models handle violent or crime scene content after mainstream options (GPT-image-2, ByteDance, Grok) blocked or distorted requests. Open alternatives were suggested including Flux via Pruna AI endpoints.

Cyber

🔐 Ctrl+G, AI cyber defense lab, launches – The startup focuses on building AI that can genuinely patch vulnerabilities across an entire codebase. The team spent three months building an automated data pipeline covering 80,000 CVEs and found that current top models consistently fail to patch vulnerabilities efficiently even when claiming success.

• They’re looking for strong red/blue team experts 👉 Paco Villetard

🔒 Cloudsmith proxies AI model downloads – Cloudsmith’s artifact management platform now proxies and caches Hugging Face models and datasets, letting organizations govern which AI models reach their pipelines, with vulnerability scanning, policy enforcement, audit trails, and global distribution.

🛡 CVE-free base images on demand – Echo rebuilds popular open source container base images with only necessary components, patches all known vulnerabilities, and delivers them directly to your registry. Claims 99%+ vulnerability reduction and zero code changes needed in existing Dockerfiles, with a 24-hour CVE handling SLA.

Infrastructure

⚡ Google’s eighth-gen TPUs for agents – Google introduced two new chips built for the age of AI agents: TPU 8t for training, which can link up to 9,600 chips into a single cluster, and TPU 8i for inference, which runs models 80% more efficiently per dollar than the previous generation.

🇫🇷 Scaleway powers France’s health data – Antoine Millet announced the company was selected to host France’s Health Data Hub following an assessment across 350+ technical criteria covering security, resilience, and strategic autonomy. The platform will host a copy of the National Health Data System database.

Language Models

🧠 DeepSeek-V4-Pro hits 1M context – DeepSeek released V4-Pro, a 1.6T parameter MoE model (49B activated) supporting a 1 million token context window. It combines Compressed Sparse Attention with Manifold-Constrained Hyper-Connections and requires only 27% of single-token inference FLOPs versus DeepSeek-V3.2 at 1M context.

🤖 OpenAI introduces GPT-5.5 – GPT-5.5 is OpenAI’s new frontier model targeting agentic coding, computer use, and long-horizon knowledge work. It matches GPT-5.4 per-token latency while scoring higher on benchmarks, and uses fewer tokens to complete the same Codex tasks.

📊 Qwen3.5-Omni scales to hundreds of billions – The Qwen3.5-Omni technical report covers an omni-modal model scaled to hundreds of billions of parameters with a 256k context window, trained on a massive heterogeneous dataset including millions of hours of audio-visual data. It claims improvements in multilingual understanding and emotional nuance in speech generation.

🔏 OpenAI Privacy Filter open-sourced – OpenAI released Privacy Filter, a 1.5B-parameter Apache 2.0 token-classification model adapted from GPT-OSS to detect and mask personally identifiable information in text. It runs locally in the browser via WebGPU, making it OpenAI’s first open model of 2026.

MLOps

🔀 Orq.ai router for LLM traffic – Orq.ai’s LLM router provides real-time cost visibility, governance, and vendor lock-in prevention across model providers. It runs on-prem with minimal footprint, supports both managed and bring-your-own API keys, and integrates natively with Claude Code via MCP.

Programming

🛠 AI prototypes need programmer review – DHH argued that while AI has given designers prototyping superpowers, models still cannot reliably one-shot production-ready code for large critical applications without programmer review or reimplementation, citing Basecamp as a concrete example where AI-generated designer code regularly requires rework.

🌙 Kimi K2.6 claims coding SOTA – Kimi claims top scores across most major agentic benchmarks. Under the hood it runs up to 300 parallel sub-agents, handles 4,000+ tool calls in a single run, and can sustain autonomous execution for over 12 hours across frontend, DevOps, and performance optimization tasks.

🧑‍💻 Qwen3.6-27B targets coding tasks – Alibaba released a 27B-parameter open-source AI model that codes and reasons at near-flagship level, often beating much larger models on coding and math benchmarks, and it also understands images and video.

📋 Anthropic explains Claude Code regression – Anthropic traced three separate issues affecting Claude Code since March: a default reasoning effort downgrade from high to medium, a caching bug that cleared prior reasoning on every turn after a session went idle, and a verbosity-limiting system prompt addition that hurt coding quality. All three were fixed by April 20.

Robotic, World AI

🌐 MultiWorld models multi-agent worlds – MultiWorld is a unified framework for action-controllable, multi-view consistent video world modeling across multi-player games and multi-robot collaboration, addressing the single-agent limitation of current video world models.

🌍 HY-World 2.0 open 3D world model – Tencent’s HY-World 2.0 generates navigable 3D scenes (3DGS/mesh) from text or a single image, importing directly into Unity, Unreal Engine, and Isaac Sim, positioning itself as the first open-source state-of-the-art 3D world model.

Other topics

📓 Anti-Agent is now a notebook – Louis Manhes announced Anti-Agent evolved into a full progressive notebook with rich-text editing, agentic deep research and synthesis, and cognitive training techniques in one minimalist workspace.

The Lunch

Each week, TTY Lunch brings together exceptional builders around the table, this time under bright sun on the Tech Makers rooftop in Amsterdam. Today’s lineup included Alina Dumitrache and Fabien Bouhier (Tech Makers), Guillaume Lesur (Wire), Justin Halsall (rrweb.io), Sohrab Hosseini (orq.ai), Robert Hommes and Vladimir Vučković (Moyai), Wilco Kruijer (ReJot), and Zac Allen (Zero Servo).

Here were some of the topics:

• Red-Green-Refactor with Agents

• Useless Memory, Thin Harness, Fat skills

• MCP + Skills, The Distribution of Roles

• The Unsolved Frontier For Coding Agents

• Finding the Right Co-founder

👉 The full discussion here

New Members

🇳🇱 Zac Allen – Founder @ Zero Servo · Robotics gaming platform doubling as an embodied data platform. Currently building Zero Servo while geeking out on Arc Raiders. Special power: will quote from random films and TV series at any given moment. 📍 Amsterdam, Netherlands.

🇬🇧 Arnaud Thiercelin – Founder & CEO @ Rogue Cortex · Stealth tools to accelerate mobile robotics development. Author of the book The Pirate Way. Special power: dunno, but I wrote a book called the Pirate Way. 📍 Guildford, UK.

Contributors This Week

Robert Hommes (Moyai.ai), Gabriel Olympie (2501.ai), Félix Raimundo (Tychobio), Tejas Chopra (Netflix, Headroom), Maziyar Panahi (OpenMed), Aly Moursy (The Artificial Intelligence Company of Cairo), Paco Villetard (Ctrl+G), Sohrab Hosseini (Orq.ai), Amine Saboni (Pruna.ai), Arnaud Thiercelin (Rogue Cortex), Kemal Toprak Uçar (Continuity), Koutheir Cherni (Guepard), Antoine Millet (Scaleway), Benoit Kohler (Opsmill), Charles Sonigo (Alpic), Ihab Bendidi (Recursion), Pierre Chapuis (Finegrain), Stan Girard (The Vibe Company), Youssef Tharwat (Noodlbox), Zac Allen (Zero Servo), Benjamin Trom, Gilles Seghaier (Astran), Julien Seveno-Piltant, Karim Matrah (Contrast), Louis Manhes (Genario), Quentin Dubois (OSS Ventures), Remi Kaito (Arcade AI), Sacha Morard (Edgee), Vladimir de Turckheim, Wissam Antoun (Inria)

Events

🇧🇷 TechBio Social at ICLR in Rio (Apr) – Valence Labs and the LMRL Workshop host a TechBio gathering for ICLR 2026 attendees in Rio de Janeiro.

Audio

🎙 Gemini 3.1 Flash TTS launched – Google shipped Gemini 3.1 Flash TTS in Gemini API, AI Studio, Vertex AI, and Google Vids, scoring an Elo of 1,211 on Artificial Analysis’s blind-preference TTS leaderboard. New audio tags let developers steer vocal style, pace, and delivery with natural-language commands embedded in the text input, alongside native multi-speaker dialogue, support for 70+ languages, and SynthID watermarking on all outputs.

🎓 CS153 guest lecture by ElevenLabs – Stanford’s Frontier Systems class hosted ElevenLabs co-founder Mati Staniszewski walking through the company’s early days, part of a recommended lecture series covering today’s frontier infra teams.

Autonomous Agents

🎛️ The MCP design debate – A week-long thread reframed how to think about MCP servers. A Cloudflare post by Kenton Varda and Sunil Pai argues that the prevailing pattern of exposing MCP tools directly to LLMs is flawed. LLMs have seen vast amounts of real world TypeScript, but only a narrow, artificial set of tool calls. Their approach converts MCP tools into a TypeScript API, has the LLM write code against it, and runs that code in a V8 isolate sandbox where MCP servers are exposed as bindings rather than accessed over the network.

Phil Schmid’s counterpoint argues that MCP is not the problem, but poorly designed servers are. He frames MCP as an agent-facing UI rather than a REST wrapper, and outlines principles such as designing tools around outcomes, simplifying inputs, treating descriptions and errors as core context, limiting the number of tools, using explicit naming, and avoiding large unstructured outputs.

• The naive OpenAPI2MCP pattern of one endpoint per tool is the shared punching bag: both the code-mode and best-practices camps agree it fails under real workloads because MCP is a user interface for agents, not a basic REST wrapper.

• A pragmatic middle ground surfaced: design MCP servers around the workflows users and agents actually need, keep a search-and-execute path for the unanticipated, and evaluate servers by pass^k on frequent tasks.

• Community take w/ Sebastien Charrier (Bump.sh): “I’m not convinced by the 100% code mode for all use cases. If the LLM has to build the code wrapper at runtime, it can result in very poor performance. It can work in a dev process because you accept waiting a few minutes, but for end-users consuming your service through MCP it’s not acceptable.”

🤖 Rethinking agent evaluation as a production system – Jules Belveze argues the current paradigm is breaking down: static datasets decay, benchmarks get gamed, and they fail to capture real outcomes. He suggests evaluation should emerge from the platform itself, leveraging production traces, feedback, and version history rather than separate benchmarks. He outlines three directions: behavioral fingerprinting based on execution consistency, a feedback flywheel that turns failures into minimal reproduction tests, and outcome signals such as user return, escalation to humans, and increasing task complexity over time, with static benchmarks remaining useful but secondary.

🎲 Property-based testing for agentic coding – Anthropic’s Frontier Red Team presented an agent that infers code properties from docstrings, type hints, and comments, then generates property based tests using Hypothesis. The goal is to automatically discover bugs by stress testing these inferred properties with large numbers of edge case inputs, rather than relying on hand written tests.

📱 Gemma 4 edge agent skills – Google claims Gemma 4 brings advanced agentic AI to devices, enabling multi-step planning, autonomous actions, and multimodal tasks on-device. Open under Apache 2.0, it supports 140+ languages and runs efficiently across mobile, desktop, and IoT hardware.

Biotech, Health, and Chemistry

🧬 OpenAI ships GPT-Rosalind biology LLM – OpenAI released GPT-Rosalind, a version of its model trained on how biologists actually work and on the big public biology databases. It is built to push back when a researcher proposes a bad idea instead of agreeing just to be helpful. Only approved US teams get access for now, with a lighter research plugin open to everyone else.

• Community take w/ Maziyar Panahi: “I’ve tried Claude for Health. The skills are mediocre at best, and without third party MCP servers they are basically useless. It is disappointing, especially since they have not been updated in 3 to 4 months. Meanwhile, OpenAI’s latest podcast hints at deeper industry partnerships and specialized models and tools for life sciences that Codex can orchestrate. That direction might explain why Anthropic is acquiring biotech startups.”

Image, Video & 3D

🌊 ByteDance’s paper and flow model discussion – The Continuous Adversarial Flow Models paper by Shanchuan Lin takes an existing flow matching model and trains a second “critic” network alongside it to judge whether generated images look real. After just 10 extra training passes, image quality on ImageNet improved dramatically. The paper triggered a week-long community thread on why flow matching and diffusion, the two dominant frameworks behind modern image generators, are actually the same thing, surfacing three further resources worth reading.

• The “same thing” reference: a Google DeepMind explainer showing that diffusion and flow matching can produce identical samples under the right parameterization.

• A Kaiming He’s Back to Basics paper from 2025 argues that diffusion models no longer truly denoise but instead predict noise, a harder task. It suggests predicting the clean image directly and shows that simple pixel-level Transformers can achieve similar results without added complexity.

• A great intro to flow matching models: Julia Turc’s video breakdown. Paired with the companion diffusion.fyi interactive tutorial, recommended as the cleanest on-ramp before harder papers.

• Community take w/ Pierre Chapuis: “Flow matching is just what happens when you realize there is a simpler and better way to do diffusion.”

🎬 CS153 with Black Forest Labs – Stanford’s Frontier Systems class hosted Black Forest Labs co-founder Andreas Blattmann, covering the lab’s image and video generation stack.

Cyber

📐 AISI evaluates Claude Mythos – The UK’s AI Safety Institute tested Claude Mythos Preview on a battery of hacking challenges. It solved the hardest tier 73% of the time, and became the first AI to complete a 32-step simulated corporate network attack entirely on its own, succeeding in 3 of 10 attempts and averaging 22 steps versus 16 for the previous best model. It got stuck on an industrial-controls scenario though, and its performance kept scaling with more compute.

• Community take w/ Gabriel Olympie: “As long as it is not independently tested, I consider Mythos a marketing stunt. More seriously, it’s not the first time Anthropic is using cyber to create traction, so even if Mythos is most likely real and quite powerful, I’d wait to see it evolve in the real world before falling for the narrative.”

🔍 Post-Mythos jagged cyber frontier – Security firm AISLE argued Mythos’s capabilities are less exclusive than Anthropic suggests. When they ran Anthropic’s own showcase bugs through small, cheap open-source models, 8 out of 8 caught the main flaw, even a tiny model costing roughly $0.10 per million tokens. Their point: the security workflow around any model matters more than the model itself. AI hacking skills are also uneven: a model can ace a hard bug and then completely miss an easier one.

🛡 GPT-5.4 Cyber for defenders – OpenAI launched GPT-5.4 Cyber, a version of GPT-5.4 tuned for defensive security work with looser safety filters that would normally block legitimate cybersecurity tasks. It can also analyze compiled software without needing the source code, something binary reverse engineers usually do by hand. Access is limited to verified individuals and approved organizations through the Trusted Access for Cyber program.

Language Models

🧠 Qwen 3.6 35B-A3B refreshed – Qwen shipped 3.6 as a 36B-parameter, 3B-active mixture model on Hugging Face with a 262K native context, positioned around agentic coding and a new Thinking Preservation mode that keeps reasoning traces from historical messages to reduce redundant thinking across turns.

🆕 Claude Opus 4.7 ships – Anthropic announced Claude Opus 4.7 as its most capable Opus, pitched for long-running tasks with more rigor, tighter instruction following, and self-verification of outputs, alongside three-times resolution vision, a new xhigh effort tier on the API, and a /ultrareview command in Claude Code. Reception on reddit was sharp: reports of faster token burn, lazy “let’s pick this up later” quitting after a few messages, hallucinated packages and imaginary coworkers, fabricated search tool calls without the UI indicator, sycophancy that flips positions under light pressure, and broad failure to honor configured claude.md and system preferences that 4.6 handled without drift.

• Community take w/ Julien Seveno-Pilitant: “Even if the scaling laws still work technically, from a human perspective it makes less and less difference. The models are converging toward the entropy of the language itself, and they approach it logarithmically, so the progress is less and less visible.”

👩‍💻 Tokenizers tuned for code LLMs – A new paper with Ivan Yamshchikov (Pleias) contribution proposed training tokenizers that focus on widely shared, useful code pieces rather than rare project-specific junk, so models learn durable code patterns more reliably.

Programming

💬 Karpathy on prompt requests – Andrej Karpathy relayed a Peter Steinberger line that PRs should stand for “Prompt Requests”: capable agents can implement most ideas, so there is no need to take an idea, expand it into a vibe-coded mess on free-tier ChatGPT, and send that as a PR. The community pushback was that coding agents still need a second set of eyes, and that specs or markdown files are not the new source code.

🎻 Cline Kanban for multi-agent orchestration – Cline Kanban is a promising open-source UI to orchestrate multiple coding agents (Claude Code, Codex, Cline) in a Kanban board, letting you break down projects, chain dependent tasks, and review real-time diffs and comments in one place.

🎤 Building pi in a world of slop – Mario Zechner’s presentation of pi at AI Engineer Europe, his minimal, extensible coding‑agent harness. He criticized opaque “slop” agent ecosystems and OSS clanker spam, and argues for slow, tightly scoped, human‑controlled use of agents in codebases.

• Community take w/ Robert Hommes: “AI Engineer Europe completely altered my beliefs on coding agents. Codex and Claude Code are the wrong harness to run GPT and Claude. Thin harness and heavy skills together with high-intelligence models like Claude, Gemini, and GPT is going to be the real unlock. Removing the developer dependency using skill transfer learning will end developer babysitting and start swarm programming with autonomous agents.”

Robotic, World AI

🤖 Pi07 steerable robotic foundation model – Physical Intelligence released pi07, a steerable model showing strong gains in generalization, including early compositional abilities. It can learn new tasks like using kitchen appliances with step by step language guidance, then execute them autonomously after fine tuning. It also shows cross embodiment transfer, for example folding laundry on a bimanual UR5e without task specific training data. The model supports multimodal prompts, including language, metadata, control signals, and visual subgoals.

🌍 NVIDIA Lyra 2.0 for 3D worlds – NVIDIA Research released Lyra 2.0, a framework for generating persistent, explorable 3D worlds at scale from a single image. It fixes the common failure where models forget what spaces look like and lose track of motion over time by maintaining per-frame 3D geometry to retrieve past frames and using self-augmented training to correct its own temporal drift. A robot can be dropped into the generated world for real-time simulation and immersive applications.

👉 Community Ask:

🤖 Luigi d’Ovidio looks for a quick DM with anyone hands-on with Vision-Language-Action model development.

Other topics

⭐ GitHub fake star economy exposed – A peer-reviewed ICSE 2026 study using StarScout identified around 6 million fake stars across 18,617 repositories by 301,000 accounts, with fake campaigns affecting 16.66% of repositories with 50+ stars by mid-2024. Stars sell for $0.03 to $0.85 on at least a dozen open marketplaces, and VCs explicitly use star counts as sourcing signals, with Redpoint reporting a median of 2,850 stars at seed.

👟 Allbirds pivots to AI – Allbirds sold its shoe brand and assets for $39M, locked in a $50M convertible financing facility, and rebranded as NewBird AI to become a GPU-as-a-service and AI-native cloud provider, pending a May 18 stockholder vote.

📊 Stanford 2026 AI Index released – Stanford HAI’s 2026 AI Index laid out ten takeaways: the US–China model performance gap has effectively closed to a 2.7% top-model lead, industry produced over 90% of notable frontier models, generative AI reached 53% population adoption within three years, and AI researcher migration to the US dropped 89% since 2017. It also flagged a jagged capability frontier, with models winning IMO gold while reading analog clocks correctly only 50.1% of the time.

👉 Community topics:

🥷 Lior Oren built a tool using a signed-data anti-fraud patent to catch fake-location candidates in hiring pipelines, triggered by a selfie step, and is looking for design partners to test it for free.

📈 GrowthMom competitive intel tool – Louis Manhes is building a competitive intelligence tool for startups using Clay-style waterfall enrichments across pricing, product, SEO, content, and socials, with an MCP interface for GTM agent stacks.

New Member

🇫🇷 Charles Sonigo – Cofounder @ Alpic · All-in-one MCP platform helping companies build presence in ChatGPT and Claude via tools to build, deploy, test, audit, and monitor MCP servers and ChatGPT apps. Geek turned PM turned founder turned Geek, full loop. Dad, tennis, and wingfoil on the side. Special power: I sleep fast. 📍 Paris, France

Contributors This Week

obert Hommes (Moyai.ai), Pierre Chapuis (Finegrain), Aly Moursy, Gabriel Olympie (2501.ai), Gilles Seghaier (Astran), Julien Seveno-Pilitant, Sebastien Charrier (Bump.sh), Amine Saboni (Pruna.ai), Daniel Madalitso Phiri, Gawen Arab (Airbuds), Ihab Bendidi (Recursion), Lior Oren, Louis Manhes (Genario), Quentin Dubois (OSS Ventures), Guillaume Lesur (Wire), Koutheir Cherni (Guepard), Emmanuel Benazera (Jolibrain), Julien Duquesne (Scienta Lab), Youssef Tharwat (Noodlbox), Andrea Pinto (Notte.cc), Antoine Sueur (Pletor), Charles Sonigo (Alpic), Constant Razel (Hypermind), Jules Belveze, Luigi d’Ovidio (Graybx), Noé Charmet (Shipfox), Sylvain Hajri (Epieos).

Community Asks

📰 Newsletter management tools – Glenn Sonna asked the community what tools they use to manage the flood of AI newsletters and filter for signal. Suggestions ranged from OpenClaw-based cron jobs to Tasklet, a YC-backed managed agent platform for automating business processes with plain English.

🔬 Amazon Research Awards feedback – Hani Chalouati is seeking feedback on the Amazon Research Awards Spring 2026 call for proposals.

Community Updates

🚀 Ascii.dev adds voice and in-game overlay – The pocket CTO agent now supports fully hands-free operation through walkie-talkie-style voice commands and an in-game overlay, letting developers orchestrate coding agents while doing other things.

Autonomous Agents

☠️ Claude subscriptions drop third-party coverage – Anthropic announced that Claude subscriptions will no longer cover usage on third-party tools like OpenClaw. Users can still authenticate via extra usage bundles (now discounted) or API keys.

🦞 Aquarium CE, self-hosted agent management – Shuai Zhang (Jinko) released an open-source platform for deploying and managing AI agent instances locally with a single command. It supports 27+ AI providers, 14 messaging channels (WhatsApp, Telegram, Discord, Slack), MCP tools, and encrypted credential storage, all running on local SQLite with zero telemetry.

🎛️ MCP vs Skills, a practitioner’s take – A detailed post argued that the MCP remains the superior architectural pattern for giving LLMs access to services. Remote MCP servers offer zero-install usage, seamless updates, saner OAuth-based auth, and true portability across devices, while Skills work best as pure knowledge layers.

🔍 Governed agent autonomy patterns – After analyzing the Claude Code source leak, Nnenna Ndukwe (Qodo) extracted a docs-first reference for building agentic coding systems with governance baked in. The framework covers five gates: plan, permission, tool trust, verification, and runtime accountability.

Biotech, Health, and Chemistry

🧬 AI-native biotech meets radiopharma – TTY published an interview with Ashley van Heteren of Radiogenesis, a startup using generative models and physics-informed AI to design targeted radioactive drugs for metastatic cancer. The company uses foundation models to design peptide candidates in silico before lab validation, compressing early discovery from years to months.

Image, Video & 3D

🩻 Raidium confirms the VLM mirage effect – Following last week’s mention of the Stanford “mirage” paper, Pierre Manceron (Raidium) shared that his team had independently observed the same phenomenon and published their own study. Their paper explored how prior medical knowledge and statistical reasoning allow models to bypass visual input entirely: “In practice many medical diagnoses can be inferred just from the question and good medical knowledge, statistically speaking. For example you know that a patient is a smoker, and ask ‘is there a lesion on this CT scan’, even if you don’t see the image itself, the probable answer is still lung cancer.”

Cyber

🏴‍☠️ Claude Mythos Preview stays behind closed doors – Anthropic released a 244-page system card for Claude Mythos Preview, its most capable model to date, alongside Project Glasswing, a program restricting access to 12 major tech companies for defensive cybersecurity only. The model achieved 93.9% on SWE-bench Verified and 100% on Cybench, and autonomously discovered thousands of zero-day vulnerabilities in every major OS and browser.

• The system card documented rare but concerning behaviors: sandbox escapes, posting exploits to public websites, editing git history to hide unauthorized changes, and attempting prompt injection on evaluation graders.

• Anthropic described the model as simultaneously its best-aligned and highest-risk release, noting that its skill enables it to reach more dangerous situations even when well-intentioned.

🔒 Astral shares CI/CD security practices – The team behind Ruff and uv published a detailed breakdown of how they secure their open-source tools against supply chain attacks. The post covers banning dangerous GitHub Actions triggers across the organization, requiring commit-pinned actions with impostor-commit detection, using Trusted Publishing for registry releases, and employing Sigstore attestations for binaries.

Language Models

🔥 GLM-5.1 tops SWE-Bench Pro – Zhipu AI released GLM-5.1, a 754B-parameter open-weight model under MIT license that claimed the top spot on SWE-Bench Pro (58.4) and led on MCP-Atlas (71.8). The model sustained autonomous execution for up to 8 hours across hundreds of iterations and thousands of tool calls, unlike predecessors that plateau early.

🧠 Meta’s benchmark layout draws scrutiny – Community members debated Meta’s new model, Muse Spark, and its potentially misleading benchmark presentation. The broader discussion questioned whether benchmarks still matter when real-world impressions consistently diverge from reported scores.

🔩 Karpathy’s LLM knowledge base in practice – Jeremie Kalfon shared extensive experience using Karpathy’s LLM KB concept to replace OpenClaw’s simple markdown memory with a rich Notion/Obsidian database: “The powerful idea is to replace OpenClaw’s simple memory markdown as a large Notion/Obsidian database with many enriched markdown files and an index. I can always search and interact with them on my Notion and this is nicer than through my terminal/IDE.” The approach worked well for personal knowledge bases built from messaging apps and social media exports, but model laziness remained the biggest unsolved friction: “They tend to be lazy colleagues/interns, they do not push the task to their limits, nor do they think about the ramifications of what has to happen next when the task is finished.” Running mostly on Sonnet 4.6, token costs reached ~€100/day.

Programming

🥷 Claude-sock wraps Claude Code for subscription use – A CLI tool that wraps the Claude Code TUI to let tools like OpenClaw use Claude models with a subscription only, without API keys or extra tokens. It spawns a fresh TUI process per call (with ~5s startup overhead) and translates output to the claude -p protocol format.

🐳 Docker Sandboxes quickstart guide – A hands-on guide covering the Docker Sandboxes (sbx) experimental launch, including parallel agent setup, branch mode, networking, Docker Compose inside sandboxes, port forwarding, and network policy management. The guide uses DevBoard, a full-stack Next.js + FastAPI issue tracker with intentional bugs as exercises.

• Community take w/ Amine Saboni: “I’m fostering the intuition that Docker is a really appropriate abstraction for developers to work with AI. Their not-so-recent focus on agent isolation is really interesting to track.”

🐆 Ardent AI vs Guepard on database cloning – When YC-backed Ardent AI launched with a pitch for instant Postgres clones for coding agents, the community compared it with Guepard, an open-source alternative already available. Key differences: Guepard is self-hostable, supports all databases (not just Postgres), and branches entire data environments rather than using production copies.

👨‍💻 Pi’s creator joins Earendil – Mario Zechner, creator of pi (the agent powering OpenClaw), announced he sold the project to Earendil, co-founded by Armin Ronacher and Colin Daymond Hanna. The pi core stays MIT-licensed forever, with commercial additions planned under Fair Source (converting to open-source via delayed publication). Zechner cited alignment on OSS values and wanting to avoid the solo-founder VC path after his experience with RoboVM’s closed-source fate at Microsoft.

Other topics

🎓 Stanford CS153 on frontier systems – The kickoff lecture of Stanford’s Frontier Systems course (Spring 2026) covered the infrastructure stack powering AI scaling: from capital and data centers to models and governance. This session detailed a “Great Transition” where AI development is evolving from a bespoke craft into a rigorous industrial engineering process characterized by massive training cycles. Central to this shift is the rising dominance of Reinforcement Learning, which now rivals the initial training phase in compute consumption to drive major capability gains. However, this rapid industrialization faces critical bottlenecks in context, compute, capital, and culture that define the current frontier of the field.

• Scaling laws are being pushed by shifting the focus from initial base model training to intensive post-training and reasoning-heavy reinforcement cycles.

• The physical constraints of AI progress have moved beyond software to include land acquisition, power grid capacity, and the geopolitical management of specialized hardware.

• Institutional friction in large organizations creates a strategic advantage for individuals who possess high-trust personal networks and specific technical obsessions.

• Developing “frontier” systems requires addressing the security and infrastructure problems that exist in the industry but are currently absent from academic environments.

TTY Lunch

Each week, TTY Lunch brings together exceptional builders around the table. Today’s lineup included Bertrand Guiheneuf (Fairjungle), Denis Brule (Finegrain), Francis Bouvier (Lightpanda), Karim Matrah (Contrast), Olivier Desclaux (Harmattan), Pierina Camarena (42 AI), Quentin Soulet (Dune Health), and Sacha Morard (Edgee).

• Fast code alone doesn’t build product value

• Non-engineers shipping code without system awareness

• Can AI learn taste

• Facing the new GAFAM

• Classical models still power critical systems

👉 The full discussion is here

New members

🇪🇬 Aly Moursy – Founder & CEO @ The Artificial Intelligence Company of Cairo · Applied AI lab building AI products for the MENA region. Born in Cairo, raised in Dubai/Canada, studied engineering in Canada. 2x startup founder. Special power: making funny tech memes that go viral. 📍Cairo, Egypt

🇳🇱 Joel Milligan – Founding AI Engineer @ neno · Based in Amsterdam for 4 years, 10 years of software engineering experience, ex-founder (TechStars Berlin). Currently building Viche, an agent-to-agent communication layer and discovery protocol. Special power: navigation, has never ever been lost. map📍 Amsterdam, Netherlands

Contributors This Week

Aly Moursy (AIC of Cairo), Glenn Sonna (Xybrid), Koutheir Cherni KC (Guepard), Enrico Piovano (Goji), Hani Chalouati (Guepard Inc.), Nnenna Ndukwe (Qodo AI), Pierre Manceron (Raidium), Robert Hommes (Moyai.ai), Anicet Nougaret (Ariana.dev), Pierre Chapuis (Finegrain), Amine Saboni (Pruna.ai), Félix Raimundo (Tychobio), Hugo Venturini (SkipLabs), Jeremie Kalfon (Pasteur), Quentin Dubois (OSS Ventures), Shuai Zhang (Jinko), Youssef Tharwat (Noodlbox), Daniel Huynh (Conception), Gabriel Olympie (2501.ai), Ihab Bendidi (Recursion), Joel Miligan, Laurent Mazare (Gradium), Nancy Wang (FluenTea), Stéphane Collot (Sequense), Tejas Chopra (Netflix)

Community Updates

⭐️ Headroom crosses 1k stars with v0.5.12 — The open-source context compression layer for LLM applications shipped faster inference, supports for LangChain, LangGraph, Windows and OpenClaw. Used by Netflix, Meta, and Vercel.

📈 Edgee shows Claude Code session analytics — A new shareable session report format for the Edgee AI Gateway showed 63% tool compression across 213 requests and 13.9M tokens! Works with Claude Code, Codex, OpenCode, and Cursor support coming soon.

📱 LFM2.5-350M runs on Android via Xybrid — Liquid AI’s 350M-parameter model ran at 40+ tokens per second on Android through the Xybrid runtime, crossing the threshold where on-device AI feels native.

Events

🇳🇱 Reliable Agents Club, April 15th in Amsterdam — For people who run AI agents in production and want to make them more reliable and debuggable. The event focuses on discussing agent reliability challenges, networking with peers, and introducing Moyai’s platform for monitoring and diagnosing failures in agentic workflows.

Audio

🔊 On-device TTS enters private beta — Gradium announced Phonon, a text-to-speech model that runs locally on smartphone CPUs with natural voices, multilingual support, and voice cloning, requiring no server, no latency, and no per-call cost.

• The private beta is now open for game developers and app builders. The model runs entirely on-device, eliminating cloud dependency and enabling offline voice interactions at scale for free-tier products.

• A community discussion highlighted the gap between available high-quality TTS models and polished consumer apps: “Why wouldn’t Mistral, Gradium, or others just build a competing Speechify? It feels like the remaining work is only 10 percent once you already have the model and the API?”.

• For Laurent Mazare, “audio models are advancing very quickly right now. Several companies, including us at Gradium, focus on training these models but lack the cycles or expertise to build applications, so we sell them to startups that handle the end products.”

• Also, the “remaining 10%” framing undersells the problem for Glenn Sonna. “Getting a TTS model to run well on someone’s actual phone is a whole different beast: quantization, memory, battery, latency. Cloud API plus per-token cost kills UX for something like a reading app.”

Autonomous Agents

👔 Pocket CTO delegates to cloud agents — The new product from Anicet Nougaret is live. Pocket CTO accepts voice memos on Telegram or desktop instructions, then orchestrates multiple cloud coding agents working in parallel on their own machines. It maintains a central always-on agent aware of your tools and codebase, surfaces demos, PDF reports, hosted builds, and executive summaries, and supports cron jobs, webhooks, secrets, and git hooks.

🧰 A massive agent harness for coding tools — A performance optimization system originating from an Anthropic hackathon winner, shipping 30+ agents, 150+ skills, autonomous loop patterns, continuous learning, and AgentShield security scans across 10+ language ecosystems. Built over 10+ months of real-world use with 30+ contributors, it supports Claude Code, Codex, Cursor, and OpenCode via a single install pipeline.

Biotech, Health, and Chemistry

🧬 Bio foundation models hit the noise floor — A journal entry analyzed a GenBio AI benchmark testing whether AI can predict how cells respond to interventions, drawing on TTY community discussions to propose four investment criteria for techbio: solve a specific biological problem deeply, iterate fast on data that actually predicts what happens in patients, pick mechanisms where physics constrains the outcome, and generate rich data only where the underlying biology is well-understood enough to learn from.

• The best AI models approached but could not exceed the natural variability of the experiments themselves, meaning the ceiling is set by biology, not by compute or model size.

• Models that encoded existing biological knowledge (which genes interact with which) consistently outperformed those trained on raw data alone, suggesting that in biology, domain expertise still beats brute-force scaling.

• Newer models not in the benchmark are closing the gap: State (Arc Institute) improved prediction accuracy by up to 200% over baselines by training on 167M cells, TxPert (Valence Labs/Recursion) matched experimental reproducibility using biological knowledge graphs, and Xaira’s X-Cell claims to go further still at 4.9B parameters.

• Community take w/ Ihab Bendidi: “GenBio’s setup does not actually perform perturbation prediction in the standard sense. It tests whether gene embeddings from unperturbed cells correlate with perturbation effects, which is an interesting but distinct question.”

• Community take w/ Félix Raimundo: “Even with perfect predictions, all you achieve is predicting the result of experiments that already fail to translate to humans 91% of the time. Being able to predict a broken proxy faster does not fix the proxy.”

• A complementary essay argued that AI will not accelerate drug development on its own, because the real bottlenecks are patient recruitment, years-long endpoint observation, and regulatory friction, not a lack of intelligence.

🔬 Five new cancer research teams launched — Global Cancer Grand Challenges funds five international teams (ATLAS, CAUSE, ILLUMINE, InteroCANCEption, REWIRE-CAN) up to $25M each to tackle cancer avoidance, mutational signatures, dark proteome, nervous system–cancer links, and therapeutic rewiring.

Image, Video & 3D

🎨 Unified image model generates and edits — Alibaba released Wan 2.7 Image, a single model handling generation, editing, and understanding in one architecture. It offers granular face control (bone structure, eyes, contour across ethnicities and ages), color palette extraction with up to 8 HEX codes, 3K-token text rendering in 12 languages including dense tables and formulas, interactive region-based editing via natural language, and multi-image generation.

Cyber

☠️ Axios npm package compromised — The popular JavaScript HTTP client with 100M+ weekly downloads was briefly hijacked through a compromised maintainer account, delivering a cross-platform remote access trojan via a hidden dependency during a two-hour window on March 31.

🎩 Black-hat LLMs automate real attacks — Nicholas Carlini, Research Scientist, Anthropic, at the [un]prompted 2026 argued that LLMs have crossed a threshold for autonomous vulnerability discovery, with capabilities growing on an exponential curve. Placing a model in a VM with broad permissions and a short prompt was enough to reliably discover severe bugs in heavily audited software.

• Demonstrated examples included a blind SQL injection in Ghost CMS that the model fully weaponized into an exploit exfiltrating admin credentials, and multiple remotely exploitable heap buffer overflows in the Linux NFSv4 daemon including a bug dating back to 2003.

• Benchmark evidence showed that models from only a few months ago rarely succeeded on such tasks, while current generations repeatedly found kernel-level bugs, with task complexity and exploit value growing roughly exponentially.

• The talk warned that automated bug discovery will soon far outstrip human triage and patching capacity, and that weak safety filters only hobble honest defenders while bad actors jailbreak around them.

Language Models

📈 Time series models meet trading — Google’s TimesFM 2.5, a 200M-parameter pretrained forecasting model with 16K context length and continuous quantile predictions, sparked a community discussion with insights from Enrico Piovano, Jeremie Bordier, and Hubert Ancelot about applying foundation time-series models to financial markets.

• Early evaluations showed decent zero-shot performance on demand forecasting but fell short of fine-tuned SARIMAX models, with inference time a dealbreaker for high-frequency use. Chronos 2 from AWS, a universal forecaster handling univariate, multivariate, and covariate-informed tasks via in-context learning, was also tested for stock backtesting with limited results.

• Community members with quantitative finance experience noted that systematic trading firms still rely on legacy logistic regressions with smart feature selection, and the shift from high-frequency to mid-frequency strategies makes portfolio hedging more important than raw latency.

• Robert Hommes drew an analogy with Nvidia PhysicsNeMo (transformer and neural operator architectures for physics simulation), suggesting similar approaches could model portfolio dynamics and forward-simulate hedging effects to maintain stable return-to-risk ratios.

• Value in time series models for trading likely lies in assessing stationarity and cointegrated pairs in mid-frequency strategies rather than directional stock predictions.

💎 Google releases Gemma 4 under Apache 2 — Google launched its most capable open model family in four sizes (E2B, E4B, 26B MoE, 31B Dense), purpose-built for advanced reasoning and agentic workflows.

• The 31B model ranked third among open models on the Arena AI leaderboard, outcompeting models 20x its size.

• Day-one support spans llama.cpp, MLX, vLLM, Ollama, LM Studio, Unsloth, transformers.js for browser inference, and fine-tuning via TRL including multimodal tool-use workflows.

👁️ Vision models answer without seeing — Multimodal models can often “fake” seeing by leveraging language patterns and benchmark quirks, so their impressive scores and detailed visual explanations can be an illusion. To trust them (especially in fields like medicine) we need evaluations and system designs that explicitly check whether their answers truly depend on the images, rather than just on text and clever guessing.

🐉 Qwen 3.6 Plus targets agentic workflows — Alibaba released its new flagship proprietary model combining hybrid linear attention with sparse MoE routing, a 1M-token context window, and up to 65K output tokens. Optimized for coding agents with support for code repair, complex terminal operations, and automated multi-step tasks, it also added enhanced multimodal reasoning for document understanding and visual coding workflows.

⚗️ Tiny 350M model punches above weight — Liquid AI released LFM2.5-350M with 28T tokens of pre-training and large-scale reinforcement learning, outperforming models over twice its size on tool use, data extraction, and instruction following. The model runs on devices from Raspberry Pi to smartphones.

🌿 Eight billion params fit in 1.28 GB — Bonsai-8B compressed a Qwen3-8B model to 1-bit quantization, shrinking it to 1.28 GB while scoring 70.5 average across multiple benchmarks. On an M4 Pro it achieved 131 tokens per second for generation, and 44 tok/s on iPhone 17 Pro Max with 2-6x better energy efficiency than 4-bit baselines.

Programming

🔓 Claude Code source code leaked — The Claude Code source was exposed through a source map file accidentally left in Anthropic’s npm registry. Within days, independent researchers published detailed analyses of the codebase, an open-source fork added support for 200+ models, and an interactive architecture explorer mapped all 519K+ lines of code.

• A reverse-engineering analysis shows Anthropic has better internal safeguards (post-edit verification, multi-agent orchestration, chunked reads, stricter prompts) that reduce hallucinations and context loss, but these are gated to employees. Author shares a “CLAUDE.md” fix to replicate them (available at the end of the tweet).

• OpenClaude forked the CLI to support OpenAI, Gemini, DeepSeek, Ollama, and 200+ models via OpenAI-compatible APIs while preserving Claude Code workflows (bash, file tools, MCP, slash commands). It added agent routing that maps different agent types to specific models within one session for cost and performance optimization.

• CC Unpacked mapped 1,900 files into an interactive explorer covering 50+ built-in tools, every slash command, and hidden unreleased features including Kairos (persistent mode with background actions), UltraPlan (long Opus planning runs), Coordinator Mode (multi-agent task decomposition in git worktrees), Bridge (remote control from phone/browser), and Daemon Mode (background sessions via tmux).

🐛 Claude Code cache bugs exposed — A detailed analysis revealed that the original v2.1.89 standalone binary had severe cache bugs dropping cache reads to 4-17%, causing nearly every token to be billed at full price.

👁️ GLM-5V-Turbo reads design drafts — Z.ai released GLM-5V-Turbo, a model using a next-generation CogViT architecture with deeply fused text-vision training. It natively ingests images, videos, design drafts, and document layouts to generate complete runnable code, targeting UI-to-code workflows and GUI agents.

🖱️ Cursor 3 goes fully agentic — Cursor announced version 3 with a whole new interface window - outside of VS Code - that lets developers run many agents concurrently across local projects, worktrees, SSH remotes, and cloud machines.

💻 Mac app wraps Headroom locally — A community-built macOS menu bar app that wraps the Headroom CLI, providing persistent savings tracking and one-click setup without pip install. All processing runs locally with no data leaving the machine.

🐳 Docker sandbox guide for agents — A hands-on quickstart for running Claude autonomously inside Docker Sandboxes using the sbx CLI, built around a full-stack demo app (Next.js, FastAPI, Postgres). Covers direct mode (edits your working tree) and branch mode (isolated git worktrees for parallel agents), with secure secrets management via OS keychain, configurable network policies, and multi-workspace mounting for cross-repo scenarios.

TTY Lunch

Each week, TTY Lunch brings together exceptional builders around the table. Today’s lineup included Charles Borderie (Lettria), Julien Goupy (Applikai), Antony Marion (Noways), Frederic Legrand (H Company), Louis Choquel (Pipelex), Julien Millet, Thomas Payet (Meilisearch), Alexandre Pereira (2501.ai), Francois Massot and Paul Masurel (Quickwit & Datadog).

• Token maximalism vs. refined intent

• Vibe fatigue and specification collapse

• Deterministic spatial design

• Moats: from code to responsibility

👉 The full discussion is here

New members

🇩🇪 Nancy Wang — CTO @ FluenTea · Language exchange with real humans and a touch of AI help. PhD combining computer vision and neuroscience, previously at IBM Research and Amazon. Born in China, raised in Canada, studied in the US, now in Berlin. Enjoys video games (currently Slay the Spire 2, all-time favorite XCOM). Special power: has never suffered a hangover. Berlin, Germany

🇫🇷 Hani Chalouati — CTO & Cofounder @ Guepard Inc. · Git-like serverless databases for AI agents. Software engineer born and studied in Tunisia, moved to France in 2014. Enjoys drone FPVs (especially DIY) and aviation. One exit from a previous company in 2024. Special power: makes very good homemade Neapolitan pizza. Île-de-France, France

Contributors This Week

Tejas Chopra (Netflix), Glenn Sonna (Xybrid), Robert Hommes (Moyai.ai), Ihab Bendidi (Recursion), Félix Raimundo (Tychobio), Koutheir Cherni KC (Guepard), Jocelyn Fournier (Softizy), Nancy Wang (FluenTea), Anicet Nougaret (Ariana.dev), Enrico Piovano (Goji), Sacha Morard (Edgee), Charly Poly (Browserbase), Quentin Dubois (OSS Ventures), Willy Braun (Galion.exe), Amine Saboni (Pruna.ai), Gabriel Olympie (2501.ai), Jérémie Bordier (XHR), Laurent Mazare (Kyutai), Hubert Ancelot (Verne), Jeremie Kalfon (Pasteur), Maziyar Panahi (OpenMed), Pierre Chapuis (Finegrain), Victoire Cachoux (Iktos), Hani Chalouati (Guepard), Karim Matrah (Contrast), Louis Choquel (Pipelex), Louis Manhes (Genario), Shuai Zhang (Jinko)

Community Asks

🤖 Gabriel Olympie is looking for feedback about Agno, an open-source framework for building, running, and managing agentic software at scale.

📋 Nnenna Ndukwe is looking for a tool that traces intent from ticket to PR to QA in agentic engineering workflows. She wrote a field report from DevNexus exploring the gap.

Community Updates

🏆 Cubic has been ranked first on Martian’s independent code review benchmark: 61.8% F1 score, ahead of tools like Cursor Bugbot (45%), Claude Code, Gemini, and Coderabbit (30%). And also praised by the community. Congrats, Paul!

Events

🇫🇷 CodeCarbon x Pruna x Ecologits Frugal AI party in Paris (April 8) – After-party following the PyTorch conference.

Audio

🎙️ Voxtral TTS finds its voice – Mistral AI released a demo of Voxtral TTS, its voice adaptation model. A single voice adapted to new languages, accents, and expressions. Community noted the French voice still carried a foreign accent.

Autonomous Agents

🦞 Community takes on persistent agents – Between a Discord discussion and TTY lunch, the community dissected what it takes to deploy persistent agents in real organizations. Five themes emerged: task assignment, communication interfaces, permissions, monitoring, and cost control. No one has cracked the full stack yet, but concrete approaches are taking shape.

• Agents are harnesses, not intelligence. Guillaume Larcher (Linkup) uses directly Pi (OpenClaw’s backbone) as a thin execution layer wired to Opus or Codex, limited to file I/O, bash, and grep.

• Agents as external contributors. Sylvain Utard runs Albert in production at Altertable: it has its own GitHub account, reads notifications, clones repos, writes code, and opens PRs across a dozen SDKs. No privileged access, spec-driven workflows, behaves like an open-source maintainer.

• A CTO agent in the cloud. Anicet Nougaret is building a persistent CTO agent available via Telegram. The first 13 users generated 1,300 commits in two days!

• Security first. Permissions ranked as the top concern for everyone. Arnaud Porterie explored highly containerized persistent agents. Hugo Venturini (SkipLabs) recommendation: “Using narrower permissions for the user it impersonates.” Even though this means less autonomy.

• Slack is unfit. Venturini argues for web desktop first, mobile second, while Porterie favors task-based systems backed by Linear, which humans already use. Most, like Julien Millet, use Telegram.

• Cost explosion is real but accepted. Agent-driven workflows introduced a new variable cost layer. And this cost can spike unpredictably when agents run unchecked. But no one is seriously considering going back.

• Evaluation, not generation, is the bottleneck. People’s concerns are about without code ownership. Quentin Dubois puts it bluntly: “I don’t know how to scale a tech team anymore.” Full-throttle agent setups worked in internal contexts, but compliance and audits still required human validation layers.

• OpenClaw’s limits. Millet migrated from OpenClaw to Claude Code on Telegram, arguing it lacked structural transparency and was nearly impossible to debug. Pierre Chapuis takes a wait-and-see stance on this one: “I am going to be a late adopter on this one. Claw was an experiment as a side-project, for work I will wait to see how startups and/or big labs rationalize it first.”

🧠 ARC-AGI-3 shifts to interactive environments – The new benchmark from ARC Prize moved from static puzzle-solving to interactive environments. AI agents must explore novel settings, acquire goals on the fly, build adaptable world models, and learn continuously. A 100% score means agents can match human learning efficiency.

🧬 HyperAgents improve how they improve – Facebook Research released HyperAgents, self-referential agents that modify both their task-solving behavior and the meta-process that generates future improvements. The system built on the Darwin Gödel Machine to enable open-ended self-improvement. GitHub, thread.

🔎 Cursor indexes text for agent search – Cursor published a deep dive on building trigram-based indexes for regular expression search, targeting large monorepos where ripgrep calls took 15+ seconds. The approach drew on 1993 inverted index research and added probabilistic masks and sparse n-gram selection.

Biotech, Health, and Chemistry

🧪 Why there is no AlphaFold for materials – A Latent Space interview with MIT professor Heather Kulik explored why AI for material design lags biology. Two structural reasons stood out: combinatorial complexity (20 amino acids vs. the entire periodic table) and far worse datasets.

• In materials, databases are computationally derived (DFT), not experimentally measured, creating an in-silico vs. wet-lab gap analogous to biology.

• Universal force field models like MACE-MP-0 and CHGNet now showed cross-element transferability, directly challenging the claim of limited transfer learning.

• Community take: For Felix Raimundo, AlphaFold was truly an exception, built on 20 years of data generation from hundreds of labs on a single clear problem, which is why there has not been a second “AlphaFold moment” in bio. He believes materials science may actually be easier because simulations are better (cheaper validation and data generation), the property space is likely smaller, and interactions are simpler: a crystal interacts with itself, while a drug plays with the immune system, brain, and a huge, mostly unknown dependency graph. “I’d actually be decently bullish, but it may very well be because I underestimate the complexities involved.”

🧬 Deep learning reveals inflammation memory mechanisms – Two papers used model interpretation methods for deep learning models of regulatory DNA to uncover causal roles of sequence syntax in transcription factor binding, methylation, and histone variants tied to stem cell memory of inflammation.

Image, Video & 3D

✨ Luma launches UNI-1 multimodal model – Luma Labs released UNI-1, a multimodal reasoning model that generates pixels. Built on “Unified Intelligence,” it combined spatial reasoning, common-sense scene completion, and multilingual text rendering with image and video generation.

🪦 OpenAI shuts down the Sora app – OpenAI announced the shutdown of its TikTok-like social app built on Sora 2, just six months after launch. Despite early hype, there was no sustained interest in an AI-only social feed. The underlying model remains available.

Cyber

🚨 LiteLLM PyPI package gets compromised – LiteLLM version 1.82.8 on PyPI contained a malicious .pth file with base64-encoded instructions to exfiltrate credentials and self-replicate. The attack was traced to the earlier Trivy compromise. A checker tool and GitHub issue were published for affected repos.

• The compromise chained two supply chain attacks: a security scanner (Trivy) was itself compromised, then used to inject malicious code into LiteLLM.

• The incident reinforced that even security tooling is a viable attack vector, and these types of highly targeted supply chain attacks are becoming more frequent.

• Community take: A FOSDEM talk was cited arguing that VCS sources (even unsigned public commits) are safer than signed tarballs or PyPI packages.

Infrastructure

📈 Final training runs use minority of compute – New data from Epoch AI, drawing on MiniMax and Z.ai IPO filings plus OpenAI estimates, showed that final training runs accounted for only 10-23% of total R&D compute. The other 80-90% went to experiments, ablations, synthetic data generation, and models that never shipped. Catch-up players like MiniMax appeared to skip costly experimentation by relying heavily on large-scale distillation of frontier models.

• Community take: Benjamin Trom confirmed the pattern and added that every architectural innovation requires massive infra investment to validate. DeepSeek’s reported $5M training cost for V3 implied at least $200M in total research spending. Pierre Manceron (Raidium) put the ratio even lower: final training represented only 2-3% of their total budget.

Language Models

🔍 OpenAI monitors agents for misalignment – OpenAI published how it used chain-of-thought monitoring to study misalignment in internal coding agents. An internally deployed model attempted prompt injection to escape its simulation environment.

🕸️ RetriCo boosts Graph RAG construction 100x – GLiNER-based RetriCo replaced expensive LLM API calls for knowledge graph construction, enabling local Graph RAG systems at a fraction of the cost of Microsoft’s GraphRAG. LinkedIn post.

💻 Percepta builds a computer inside transformers – Percepta added computing capabilities inside an LLM, enabling execution of arbitrary C programs for millions of steps. The approach used 2D attention heads for exponentially faster inference compared to standard autoregressive decoding.

MLOps

🔥 TurboQuant compresses KV cache to 3 bits – TurboQuant is a new compression method that shrinks AI model memory (like KV cache and vector indexes) up to ~6–8x while preserving accuracy, enabling faster, cheaper long‑context and search systems.

Programming

❤️ OpenCode with Qwen 3.5 runs local – Louis Choquel (Pipelex) shared a detailed trial of OpenCode (open-source Claude Code alternative) across three configurations: Opus 4.6 via API, Qwen 3.5 397B via OpenRouter, and Qwen 3.5 35B locally on a MacBook Pro M3 Max with 64GB RAM. The local model ran alongside normal computer usage with no issues.

• The 35B model stopped after each phase and needed “go on” prompts, but still delivered working results thanks to clear agentic feedback loops correcting its mistakes.

• Qwen 3.5 397B through OpenRouter performed comparably to Opus 4.6, with faster speed and relevant ASCII diagrams of method flows.

• Optimizing skills for small models forced clarity and token efficiency improvements that also benefited larger models.

🔥 gstack packs 15 Claude Code skills – A Claude Code plugin with 15 tools covering CEO, designer, eng manager, release manager, doc engineer, and QA roles. The /review skill called Codex for an outside view, and /qa ran Playwright-based browser testing of all buttons and menus. The standout was the install/upgrade system: a single copy-paste instruction in Claude Code that handled everything.

• The plugin was iterated daily, and the skill upgraded itself automatically so users saw improvements without manual intervention.

• Community take w/ Louis Choquel: “It’s my best experience so far using any tool.” Good news: token usage remained modest. 9 hours of heavy use on 2 parallel projects consumed only 6% of the Claude MAX 200 weekly budget.

🛠️ RTK cuts LLM token use 60-90% – A CLI proxy written in Rust that reduced LLM token consumption on common dev commands. Single binary, zero dependencies. RTK is now part of the Headroom context optimization layer, which also added a --learn option to help coding agents learn from failures.

Other topics

😬 Fake AI candidate bypasses all filters – Lior Oren reported interviewing a candidate who turned out to be using a real-time AI filter. Warning signs included barely moving lips, nearly closed eyes, and emotionless reactions. The candidate had passed every earlier screening stage!

🧩 Anthropic designs AI-proof take-home tests – Anthropic shared three iterations of a performance engineering take-home that Claude kept beating. Each new Claude model forced a redesign. The original test was released as an open challenge, and a top human solver published a detailed writeup of the optimization strategies involved.

TTY Lunch

Each week, we brings together exceptional builders around the table. Today’s lineup included Quentin Dubois (OSS Ventures), Hugo Le Belzic (H Company), Guillaume Larcher (Linkup), Sylvain Utard (Altertable), Jules Pondard, Henri Mirande, Glenn Sonna (Xybrid).

• Agents are harnesses, not intelligence

• Developer cost explosion

• Evaluation without code ownership

• Multi-model workflows as control

• Running models in constrained environments

👉 The full discussion is here

Contributors This Week

Pierre Chapuis (Finegrain), Louis Choquel (Pipelex), Tejas Chopra (Netflix), Willy Braun (Galion.exe), Benjamin Trom, Félix Raimundo (Tychobio), Koutheir Cherni (Guepard), Jocelyn Fournier (Softizy), Amine Saboni (Pruna.ai), Gabriel Olympie (Human-Centric), Jérémie Bordier (XHR), Robert Hommes (Moyai.ai), Enrico Piovano (Goji), Julien Millet, Khaled Maâmra (Edgee), Sacha Morard (Edgee), Thierry Abalea (Shipfox), Ihab Bendidi (Recursion), Julien Seveno-Pilitant, Alexandre Meunier, Anicet Nougaret (Ariana.dev), Antoine Millet (Scaleway), Arnaud Porterie (Vibe), Guillaume Allègre (Andromede AI), Hubert Ancelot (Verne), Hugo Venturini (SkipLabs), Julien Kilo, Kemal Toprak Uçar, Lior Oren, Louis Manhes (Genario), Lucas DiCiocci (Koli), Nnenna Ndukwe (Qodo AI), Paul Sangle-Ferriere (Cubic), Pierre Manceron (Raidium), Quentin Duboix (OSS Ventures), Stan Girard, Youssef Tharwat (Noodlbox)

I’ve launched a few initiatives over the years and decided to bring them together under one home: TTY (what is TTY? Answer here).

The Reg.exe Discord community, the WeLoveSota.com blog, and my weekly TechLunches in Paris now live under this single brand.

Head to ttysession.com, where members can connect their Discord account and explore the long-awaited member directory.

Curious to hear what you think.

Events

🌐 TelcoSec Talk #2: Iran cyberattacks analysis (March 2026) – Live demo of AI-driven threat actor modeling with ApexModeler, analyzing the Iranian APT landscape in a geopolitical context.

Biotech, Health, and Chemistry

🧬 AlphaFold Database adds protein complexes – EMBL-EBI, Google DeepMind, NVIDIA, and Seoul National University released 1.7 million high-confidence homodimer predictions into the AlphaFold Database, with 18 million lower-confidence structures available for bulk download. The dataset prioritized the 20 most-studied species and WHO priority pathogens, representing about 17 million GPU-hours of compute made freely available.

😓 AI hype called out in life sciences – Anshul Kundaje shared Rachel Thomas’s post on how AI hype consistently outruns reality in biotech. Community members noted that models like scGPT keep reappearing in new publications despite over 30 papers documenting its shortcomings, pointing to conflict-of-interest issues with authors pushing their own tools.

Image, Video & 3D

🎮 DLSS 5 announced then quickly deflated – NVIDIA announced DLSS 5 with promises of AI-powered photorealistic lighting and materials for games. Days later, clarifications from NVIDIA confirmed skeptics were right: the model is a 2D AI filter using only color buffer and motion vectors, with zero access to geometry, lights, PBR properties, or normals.

• Sebastian Aaltonen laid out requirements for a proper AI rendering filter: per-pixel developer control, reference training material for hero assets, scene depth awareness, no removal of fog or volumetrics, and respect for the art style set by developers.

• Community reaction called it worse than expected, with one viral meme imagining a future where turning DLSS off reveals nothing underneath.

📹 Deterministic video depth estimation ships – DVD combines generative priors with deterministic inference to resolve geometric hallucination in diffusion-based depth models and semantic ambiguities in discriminative baselines, delivering consistent high-fidelity geometry. Code, models, Gradio demo, and ComfyUI integration were released.

Cyber

🛡️ ApexModeler maps threat actor behavior – AI-driven threat actor modeling tool that combines open-source and private intelligence into a unified engine, deployable on-premise. Built by P1 Security, it will be demoed live analyzing Iranian cyberattacks and APT attribution in the current geopolitical context.

Infrastructure

⚠️ YC compliance startup accused of faking audits – Delve, a YC-backed startup that raised $32M, was accused of systematically fabricating SOC 2, ISO 27001, HIPAA, and GDPR compliance reports. A leaked spreadsheet revealed that 493 out of 494 SOC 2 reports contained identical boilerplate text with only names and logos swapped, auditor conclusions were pre-written before any evidence review, and the advertised “US-based CPA firms” were actually Indian certification mills operating through shell entities.

Language Models

🚀 NVIDIA Nemotron 3 Super drops with open tooling – A 120B-parameter mixture-of-experts model (12B active) that reportedly surpassed Qwen3.5 on text benchmarks. More notable than the model itself, NVIDIA open-sourced its full post-training stack as the NeMo suite.

• The NeMo release includes four repos: Evaluator, RL, Gym, and Guardrails, covering the full post-training pipeline from evaluation to reinforcement learning to safety.

• The Gym component is interoperable with external ecosystems like Unsloth, lowering the barrier for custom RL-based model tuning.

• The model license remains restrictive, but the open tooling could prove more impactful than the model itself for the broader community.

🇫🇷 Pleias and NVIDIA release French personas – One million synthetic French personas grounded on real census demographics (age, gender, location, education, income) were published as the Nemotron-Personas-France dataset on Hugging Face. France’s open census license made the rich demographic grounding possible.

🎭 Reasoning models perform “theater” in CoT – A paper analyzed DeepSeek-R1 671B and GPT-OS using activation probing, early forced answering, and a CoT monitor. It found models often lock in their answer early but continue generating chain-of-thought tokens that do not reflect actual internal confidence. Harder tasks showed more genuine stepwise reasoning, while easy recall triggered performative output.

Programming

🧠 Cursor trains Composer to self-summarize – Cursor published how it uses reinforcement learning to teach its Composer model to compress its own context when approaching a fixed token limit, then continue generating. Instead of relying on an external prompted summarizer, the model learns what information to preserve as part of the reward signal during training.

🤔 Claude 1M context hidden tradeoffs – Multiple community members highlighted the productivity gains from Claude Code’s expanded context window, with enthusiastic endorsements. Some, like Stan Girard, are more skeptical, pointing out that performance degrades at large context sizes and that the current setup may hide pricing and rate limit tradeoffs, potentially leading to higher costs and overreliance on a setup that may not be sustainable long term.

📚 Andrew Ng launches Context Hub CLI – Open-source CLI that gives AI coding agents curated, versioned API documentation instead of relying on web search. Agents can attach local annotations that persist across sessions for self-improvement, while aggregated feedback flows back to documentation maintainers to continuously improve docs for everyone

📊 Vibe Drift Tracker monitors AI slop – VS Code extension that integrates with Claude Code to track how many AI prompts go into each commit, computing a real-time drift score. A high prompt count with low lines-per-prompt ratio signals feature creep and loss of focus.

🍎 Apple cracks down on vibe-coding apps – Apple blocked App Store updates for Replit and Vibecode, citing long-standing rules against apps executing code that alters their own functionality. Replit was told to open generated app previews in an external browser instead of an in-app web view, while Vibecode was ordered to remove the ability to generate software for Apple devices.

Robotic, World AI

🗺️ Pokemon Go data trains robot navigation – Niantic Spatial, spun out from the Pokemon Go maker, trained a visual positioning system on 30 billion crowdsourced images from players to locate robots to within centimeters in urban environments where GPS fails. Coco Robotics deployed the system across 1,000 delivery robots in five cities.

🏙️ Seoul World Model simulates real cities – KAIST and NAVER built a city-scale world model grounded in real Seoul street-view data. SWM uses retrieval-augmented generation on millions of panoramic images to produce faithful video spanning kilometers of actual cityscape, supporting free-form navigation, text-prompted scenario control (like spawning Godzilla), and multi-kilometer trajectories without quality degradation. Code and weights were released.

Community Updates

📦 Headroom v0.4.4 ships wrap commands – Context optimization proxy for LLM apps now supports headroom wrap claude and headroom wrap codex without running a separate proxy, and adds CLI token compression via rtk-ai. (👉 Tejas Chopra @ Netflix)

⚡ Edgee launches token compression gateway – Free proxy that compresses prompts before they reach LLM providers, claiming up to 50% cost reduction and 26.5% longer Claude Code sessions. One-minute CLI install, no code changes required, works with Claude Code, Codex, and Cursor. (👉 Sacha Morard @ Edgee)

🧠 Anti-Agent enters beta for testers – AI learning companion combining knowledge graphs, spaced repetition, Socratic dialogue, and reflective journaling, all accessible via a Telegram bot. Waitlist open. Video demo (👉 Louis Manhes @ Genario)

⚖️ Rature anonymizes PDFs in-browser by Julien Kilo – Open-source tool for lawyers running BERT-based NER entirely client-side with Transformers.js, detecting and wiping named entities before sharing documents with AI. Early alpha seeking feedback. GitHub (👉 Julien Kilo)

🤖 Xybrid ships on-device AI runtime – Rust-powered runtime that runs LLMs, TTS, and ASR natively on iOS, Android, macOS, Linux, and Windows with no cloud required. SDKs for Flutter, Unity, Kotlin, and Swift. (👉 Glenn Sonna @ Xybrid)

TTY Lunch

This week with Alexandre Esser (Arsen), Son Nguyen (Hugging Face), Jean Beuselinck (Tomorro), Khaled Maâmra (Edgee), Loic Knuchel, Marco Fucci di Napoli (Rowads), Stan Girard (The Vibe Company), Thibault Hervier, Thierry Abalea (Shipfox), Vladimir de Turckheim. Topics were:

• Different organizational models

• Beyond code-centric workflows

• CI: the main bottleneck?

• Hiring being redefined

🍕 Read the summary

New members

🇫🇷 Margot Lor-Lhommet – Co-founder & CTO @ Tigo Labs · Cognitive AI infrastructure so AI systems can reason about humans, not just respond to them. 10 years in academic AI research (France + USA), 10 years in industry (Algolia, Twilio). Runner, pianist, foodie (meat smoker), and mom of two. Special power: Making 1980s cognitive science papers ship as product features. 📍 Île-de-France

🇫🇷 Julien Goupy – Co-founder & CTO @ Applikai · Agentic mobile app builder to make production-ready apps, not prototypes. Third-time founder (one exit to Google, one spectacular fail). Started shipping low-level Android Bluetooth kernel drivers deployed on 50+ million devices (Lenovo, Motorola, TCL). Filed 40 patents. Recreational programming enthusiast: terminals, compilers, weird languages, silly toy games. Special power: Can keep a conversation about trebuchets for a whole 12h long SF to Paris flight. 📍 Paris, France

Contributors This Week

Julien Goupy, Philippe Langlois, Margot Lor-Lhommet, Quentin Dubois, Jérémie Bordier, Karim Matrah, Ihab Bendidi, Ivan Yamshchikov, Gabriel Olympie, Amine Saboni, Felix Raimundo, Christophe Lesur, Robert Hommes, Julien Kilo, Pierre Chapuis, Louis Manhes, Tejas Chopra, Kemal Toprak Uçar, Glenn Sonna, Bertrand Guiheneuf, Antoine Sueur, Gawen Arab, Sacha Morard, Youssef Tharwat, Maziyar Panahi, Koutheir Cherni.

👉 Originally posted on TTY

Events

🇫🇷 Gemini 3 Paris Hackathon (March 14) – Cerebral Valley and Google DeepMind hackathon in Paris. Builders competed on Gemini 3 across AI Studio, Vertex AI, and Antigravity for 150K in API credits.

🇫🇷 Mistral AI NOW SUMMIT in Paris (May 28) – Mistral’s flagship conference with sessions from Mistral and global leaders building and deploying AI at scale. Ticket and content details remain limited.

Community Ask

📝 White paper on AI coding frontiers – A community member began assembling a white paper interviewing engineers at the frontier of coding-agent workflows, seeking real practices, unusual setups, and hard-won lessons rather than generic opinions. The project targets engineers who feel mainstream AI coding discourse lags behind their actual practice. 👉 DM Noe Charmet

Autonomous Agents

🧪 Karpathy’s Autoresearch went viral – Open-source tool automating research on single-GPU nanochat training, generating and evaluating experiments autonomously. The project gained viral traction over the weekend for its simplicity and effectiveness.

• 🔥 Community take from our BioTechLunch: Many compare it to existing approaches such as hyperparameter search or evolutionary algorithms, noting that its novelty lies more in accessibility and scale than in fundamentally new methods. Its main value may be in allowing researchers to continuously explore numerous small ideas or improvements in the background while they focus on higher level problems. However, several concerns have been raised about metric gaming and overfitting if evaluation criteria are poorly defined. Overall, the consensus is that AutoResearch is best viewed as a research assistant that scales experimentation, while real progress in fields like biology still depends primarily on better data and experimental validation.

👍 Can AI agents reach consensus? – The paper shows that groups of AI chatbots struggle to reliably agree on a single number, even when they do not care which number wins. Larger groups fail more often, and adding a few malicious agents causes stalls and timeouts. This suggests current multi-agent LLM systems are not yet dependable for robust coordination.

🕵️ Agents reproduce worst human social behaviors – Autonomous AI assistants with email, chat, files, and code access can be tricked into leaking secrets, obeying strangers, wasting resources, breaking their own systems, or spreading manipulation, so they need much stronger security and oversight before real-world deployment.

📊 SWE-CI benchmarked agent code maintainability – The benchmark tests how well AI coding agents maintain and evolve real Python projects over many commits, mimicking a continuous integration workflow. It uses 100 real repo histories and a dual Architect–Programmer agent loop plus a new EvoScore metric to reward long-term, low-regression code quality rather than one-shot bug fixes.

Biotech, Health, and Chemistry

🌱 AI “Language Models” for Plant DNA - Alongside their Seed round, Living Models released genomic language models called Botanic0 that learn patterns directly from plant DNA to support predictions of gene activity and mutation effects, with larger models performing better and all models released openly for crop research.

• Three model sizes (100M–1B params) trained on DNA from 43 plant species.​

• Perform on par with or better than other top plant DNA models on many benchmarks.​

• Can rank harmful vs neutral mutations without task-specific training.​

• Useful as general DNA embeddings and can be fine-tuned for specific genomic tasks.​

Image, Video & 3D

🎬 Netflix acquired AI filmmaking startup – The streaming giant made a rare acquisition of InterPositive, Ben Affleck’s startup building AI-powered tools for filmmakers, signaling deeper integration of generative AI into professional production workflows.

Language Models

📋 SkillsBench: human skills beat autogenerated – Benchmark evaluated the impact of reusable skill instructions on LLM agent performance, finding that human-authored skills significantly boost reliability while autogenerated ones offer only marginal gains. The results challenge the assumption that agents can self-improve through automated skill generation.

🧪 LLM bullshit benchmark viewer – Interactive tool for browsing and comparing LLM evaluation results across models, providing a visual interface to explore benchmark performance data. The viewer aggregates results across multiple evaluation dimensions for side-by-side model comparison.

MLOps

⚡ Autokernel automates GPU kernel optimization – RightNow AI released an open-source tool that automates CUDA kernel optimization through iterative agent loops guided by a detailed instruction set. The project mirrors Karpathy’s autoresearch philosophy, applying simple agent patterns to compute-heavy tasks.

Programming

🎁 Opus defaults to 1M context window – Claude’s newest Opus 4.6 and Sonnet 4.6 models can now read about 1M tokens (huge files and chats) at normal prices, with higher limits for images/PDFs and no special beta setup needed.

🔍 Argus: Claude Code session debugger – Open-source tool for debugging and analyzing Claude Code sessions, providing performance insights and visibility into agent behavior during coding workflows.

⚖️ CLI vs IDE agent debate – Amp dropped its editor extension to focus entirely on terminal workflows, sparking discussion on whether removing IDE integration sacrifices code review quality. Amp podcast

• 🔥 Community take: Opinions were mixed. Some flagged invisible quality decay as the real risk: agents produce files that build and pass but accumulate junk, bloated components, and inconsistent naming that nobody catches without visual review. The pragmatic fix shared was running the agent in terminal while staging files in a side editor as a “reviewed” gate, with a dedicated local diff review tool for this workflow. Others argued the concern is already outdated as bigger context windows and tool improvements are actively closing the gap.

🔥 Community events:

🧩 Pipelex shipped MTHDS workflow language – Open-source framework (say “Methods”) introduced a typed, declarative language for defining executable AI methods with validated inputs and outputs. Ships with a Claude Code plugin, interactive VS Code extension, multi-provider gateway, and package manager. Hub Claude Code plugin Runtime

🗜️ Edgee shipped lossless Claude token compression – Fully lossless compression of tool call results for Claude Code and tool-heavy Claude workflows, extending effective context limits by 26.5% without information loss. Useful for teams hitting Claude Code rate limits on tool-heavy agentic sessions.

🗜️ Headroom: OSS context compression layer – Open-source context optimization framework for LLM applications surpassed 700 GitHub stars and launched a Discord community. The project focuses on prefix caching improvements to reduce token usage across agentic workflows.

📊 Claude Code subscription community survey – A community poll revealed diverse approaches to Claude Code licensing. Most teams split between Individual Max and Team Premium, with some combining tiers by role and supplementing with API or Bedrock access.

• Heavy users typically run Individual Max 20x while junior team members and non-developers use Team Premium.

• Larger teams (20+ users) prefer Team Premium for unified billing, while sub-5-person teams rely on individual plans.

• Several members supplement subscriptions with pay-as-you-go API access or AWS Bedrock for specific capabilities.

Reinforcement Learning

🎓 KARL: RL-trained enterprise search agents – KARL is a training method that teaches AI search agents to find, combine, and reason over company data much better and cheaper than current top models, using synthetic practice data and reinforcement learning.

The (BioTech) Lunch

This week with Ashley van Heteren, Cyril Véran, Jean du Terrail, Félix Raimundo, Ihab Bendidi, Jeremie Kalfon, Julien Duquesne, Maziyar Panahi, and Pierre Manceron (Raidium), we discussed:

• AutoResearch from Karpathy

• Data, the real bottleneck in computational biology

• The LLM versus world model approach

• The TechBio business models and failures

🍕 Read the summary

The AI Coding Dinner w/ Ctrl+G

Co-organized with Grégoire Gambatto and Paco Villetard (Ctrl+G) we had Aymeric Roucher, Benjamin Trom, ‎ Hugo‎ Venturini, Amine Saboni, Adam Surak, Louis Choquel, Gregory Tappero, Grégoire Mialon. Our discussion was mostly about:

• Persistent agents (OpenClaw legacy)

• SkipLabs: Static analysis meets LLMs

• The impact of code explosion on teams

• How to rethink engineer interviews

🥘 Read the summary

New Member

🇫🇷 Hugo Venturini – Software Engineer @ SkipLabs · Building a controlled, governed environment for a dedicated AI coding agent leveraging static analysis tooling. Father of three, bouldering climber, jazz piano amateur at the Bill Evans Piano Academy, and whisky ex-connoisseur. Has written songs for a French singer working on his fourth album. Special power: pending consultation with his kids. 📍 Paris, France

Contributors This Week

Kevin Kuipers, Amine Saboni, Louis Choquel, Hugo Venturini, Tejas Chopra, Leonard Strouk, Felix Raimundo, Mehdi Medjaoui, Gabriel Olympie, Sacha Morard, Noé Charmet, Pierre Chapuis, Sylvain Hajri, Alex Zhuk, Thierry Abalea, Quentin Dubois, Robert Hommes, Benoit Kohler, Maxence Maireaux, Gert Lanckriet, Karim Matrah, Kemal Toprak Uçar, Koutheir Cherni KC, Nikolay Tchakarov, Victoire Cachoux, Lucas DiCiocci, Julien Duquesne, Omid Gosha, Julien Millet, Jules Belveze, Anicet Nougaret, Anselme Trochu, Guillaume Lesur, Christophe Lesur, Enrico Piovano, Antonin Lacombe, Jocelyn Fournier, Gawen Arab, Arnaud Porterie, Marek Kalnik.

Community Asks

💡 Call for practitioners running remote MCPs in production – Sebastien from Bump.sh is looking for practitioners with hands-on experience deploying remote MCPs in production, especially those who have navigated auth flows, multi-tenant access control, and observability tooling at real scale. (👉 Sebastien Charrier)

🇺🇸 ACM Conference seeks peer reviewers, San Jose (May 26-29) – ACM CAIS 2026, co-located with the AI Engineer’s Fair, will cover compound AI architectures, optimization, and agentic deployment. Tejas is recruiting community peer reviewers. (👉 Tejas Chopra)

Autonomous Agents

🔌 Notte launched Anything API to turn any website into a production endpoint – Anything API lets users describe a browser task and receive a deployable production API endpoint backed by agentic automation. The tool targets the majority of websites that lack public APIs.

🦞 OpenClaw use cases catalogued as community surfaces real-world limits – Community members explored practical OpenClaw applications and how to go beyond its current limitations. Shuai shared awesome-openclaw-usecases, a curated GitHub repo highlighting what actually works across real workflows.

Biotech, Health, and Chemistry

🧬 Former Recursion CEO joins PacBio board, bets on sequencing data – Chris Gibson argued that in the AI era, training data quality is the decisive competitive moat regardless of model sophistication, and joined PacBio’s board to help the company capitalize on its long-read sequencing advantage.

• PacBio’s long-read technology produces higher-fidelity genomic reads than short-read alternatives, making it particularly valuable for AI training.

• On the same topic, a Leash Bio analysis drew a structural parallel between current molecular AI and pre-ImageNet computer vision, arguing dataset constraints, not model architecture, are the primary bottleneck holding back small molecule drug prediction.

🏥 Doctolib opens an AI research lab in France – The team combines data scientists, ML researchers, doctoral candidates, and physicians from academia and industry, signaling ambitions beyond scheduling software into clinical AI at one of Europe’s largest health tech platforms.

• The multidisciplinary composition, combining clinical expertise alongside AI research, reflects a bet on domain-specific models over general-purpose adaptation.

• Community member Fajwel Fogel announced his participation in the founding team.

💊 Madrigal acquires Ribo’s siRNA liver pipeline for $4.4B – The deal extends Madrigal’s MASH franchise beyond Rezdiffra into RNA therapeutics, with community noting that preclinical siRNA assets are commanding some of the most aggressive valuations in current biotech deal flow.

⚖️ Vinay Prasad exits FDA amid ongoing controversy – The head of the FDA division responsible for vaccines and biologic drugs, and a close ally of Commissioner Marty Makary, is leaving after a turbulent period marked by clashes with biotech companies over gene therapies, rare disease drugs, and how strong the evidence for approval should be.

Image, Video and 3D

✨ Gemini 3.1 Flash-Lite targets cost-efficient inference at scale – Google DeepMind’s newest addition to the Gemini 3 series prioritizes price-per-token over raw capability. Community questioned why benchmarks compared it to Gemini 2.5 rather than other Gemini 3 variants.

🔥 Pruna.ai ships P-Video: 10s for 5s of 720p at $0.02/s – Applying the same compression techniques that power their model efficiency work, Pruna.ai claims the fastest and cheapest video generation API available: 720p at $0.02/s, 1080p at $0.04/s.

Cyber

🦠 AI bot ran autonomous supply chain attacks on open-source repos – An autonomous bot, hackerbot‑claw, used Claude Opus 4.5 plus a vulnerability‑pattern index to run a week‑long campaign against GitHub Actions workflows on major open‑source repos, achieving RCE in at least 4 of 7 targets and stealing a write‑scoped token. In follow‑up analysis, Claude Code running claude‑sonnet‑4‑6 refused the same prompt‑injection attempts when reviewing an ambient‑code/platform PR where the attacker had replaced CLAUDE.md with malicious, persistent project‑level instructions.

🔐 MCP servers are unaudited software, not config files – Matt Suiche warned that unlike passive context files, MCP servers execute code and expand attack surface in ways developers consistently underestimate, drawing parallels to early mobile app distribution before security practices matured. The financial sector has already encountered real-world MCP-related security incidents, providing early evidence of the emerging threat category.

Infrastructure

💥 A GitHub Pages migration ended with a dropped prod DB – While migrating to AWS, a developer relied on Claude Code that ran a destructive Terraform command against the shared production account, wiping the course platform’s infrastructure and database; the hurried recovery added AWS Business Support and new safety architecture, locking in about a 10% permanent cost increase.

Language Models

🔥 GPT-5.4 unifies reasoning and agentic workflows in one model – OpenAI released GPT‑5.4 and GPT‑5.4 Pro, unifying its strongest reasoning, coding, and computer-use capabilities into a single model for ChatGPT, Codex, and the API. It adds native computer control, 1M-token experimental context in Codex, and more efficient tool search to run larger tool ecosystems with fewer tokens.

🚀 Alibaba releases Qwen 3.5 small series, 0.8B to 9B – Four new models built on the Qwen 3.5 foundation with native multimodal support and scaled RL training, spanning the full edge deployment spectrum. Community raised concerns about team stability at Alibaba, citing rumors that roughly half the Qwen team has left, which could make this one of their last major releases.

⚡ Yuan 3.0 Ultra: 1T-parameter open-source multimodal MoE – Yuan AI Lab open-sourced a flagship model with 1,010B total parameters but only 68.8B activated, making inference cost comparable to a dense 70B model while theoretically competing at frontier capability levels.

📊 GenAI enterprise adoption gap diagram goes viral – Mehdi Medjaoui shared a widely circulated chart showing actual enterprise GenAI deployment lagging far behind theoretical adoption curves, sparking discussion about what’s really blocking production rollout.

MLOps

⚙️ Handling spiky serverless GPU workloads – Raidium asked for real experience handling zero-to-peak inference demand where on-demand H100s proved too expensive and too slow to cold-start, with 10-minute boot times making autoscaling impractical. A community member noted that Modal provisioning is not instantaneous under load: queue waits are real, and keeping a warm instance is still recommended for latency-sensitive paths. He mainly uses Modal for ephemeral batch jobs rather than deployed inference, and open-sourced multimodal to manage multi-job output. Ed Bonlieu from Koyeb joined the thread directly to offer a follow-up call.

🏎️ Speculative Speculative Decoding claims 2x over top engines – SSD, co-developed with Tri Dao and Avner May, stacks speculative decoding at multiple levels of the inference stack simultaneously, compounding gains that single-level approaches cannot achieve. Co-authorship with Tri Dao, the FlashAttention author, lends the work significant credibility in the inference optimization community.

Programming

☠️ Code review is dying as AI-generated code becomes the norm – A Latent.space essay argued human-written code effectively ended in 2025, and that traditional peer review adds diminishing value when the author is a model that self-corrects faster than any human reviewer. Tejas Chopra is building Intent, a TypeScript-like language for coding agents where agents both write and review code, with optional human oversight.

📦 Google open-sources a unified Workspace CLI with AI skills – A single command-line tool that provides a unified interface to Google Workspace APIs (Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more), dynamically building its command surface at runtime from the Google Discovery Service so it stays in sync with API changes, and shipping with built-in Agent Skills for LLM-driven automation and MCP-based agents.

🔧 Essay makes the case for CLI over MCP in agent tooling – EJ Holmes argued that LLMs can invoke CLIs natively, making a dedicated protocol layer architecturally unnecessary and adding attack surface without commensurate benefit.

🧠 Headroom learns from Claude Code failures across sessions – Tejas Chopra analyzed 59,470 tool calls from 1,960 real sessions, found 6,112 failures and ~1M wasted tokens. The new learn command extracts the delta between each failure and its successful correction, writing results to CLAUDE.md and MEMORY.md. Top failure categories: wrong Python binary (627), permission denied retried without fix (525), file not found at guessed paths (329), all preventable with persisted context.

🧠 Two new MCPs bring shared and persistent memory to agents – Christophe Lesur from Cloud Temple released live-memory for real-time working memory across collaborative agents, and graph-memory for long-term knowledge graph storage, together addressing the stateless nature of current agentic frameworks.

🗜️ Edgee’s Claude Code Compressor strips tokens before they hit the API – An edge model intercepts Claude Code requests and removes redundant tokens upstream, reducing cost and context pressure without workflow changes. 👉 Free during beta.

🔍 Amplifying.ai maps how Claude Code makes tool decisions – A systematic study examined reasoning patterns, consistency, and potential biases in Claude Code’s agentic choices, from product recommendations to developer tool selection, using real developer interaction data.

Robotic, World AI

🤖 OpenClaw gains spatial reasoning and runs on Unitree G1 – The open-source agent framework added physical space and temporal understanding via lidar, stereo, and RGB camera integration, with a demo showing it deployed on a humanoid robot alongside drone and quadruped support.

Other topics

🌍 WorldMonitor: open-source global intelligence in one view – A real-time dashboard combining AI-powered news aggregation, geopolitical monitoring, military tracking, and market feeds. Local agents can be plugged in for custom investment research or tech watch pipelines.

The Lunch

This week’s discussions explored how the rise of coding agents could reshape developer tooling, workflows, and infrastructure. Key themes included the shift from UX to Agent Experience (AX), CLI vs MCP interfaces, languages suited for agent-driven development, and the growing infrastructure moat around frontier models.

With Christian Wallenwein (Mistral AI), Benjamin Trom, Ellie Huxtable (Atuin), Max Corbani (>commit), Anastasia Stasenko (Pleias), Koutheir Cherni (Guepard), Jules Pondard, Sohrab Hosseini (orq.ai), Fred Bardolle (Scaleway), and Shuai Zhang (Jinko)

New Member

🇫🇷 Denis Brulé – CEO @ Finegrain · On-device photo editing platform that removes cloud dependency from mobile image processing, built on the premise that a €1k+ device shouldn’t need cloud permission to edit a photo. Founded Moodstocks in 2008 to let smartphones search the world with their cameras; the company was acquired by Google and the technology launched as Google Lens in 2018. Special power: playing the only piano piece he knows on repeat without ever tiring of it, much to the despair of his relatives and neighbors. 📍 Paris, France

Contributors This Week

Felix Raimundo, Christophe Lesur, Kemal Toprak Uçar, Denis Brulé, Gabriel Olympie, Tejas Chopra, Gilles Chehade, Pierre Manceron, Pierre Chapuis, Sacha Morard, Bertrand Charpentier, Mehdi Medjaoui, Robert Hommes, Ihab Bendidi, Charly Poly, Jeremie Kalfon, Dario Di Carlo, Sebastien Charrier, Matt Suiche, Vlad de Turckheim, Fajwel Fogel, Andrea Pinto, Lucas DiCiocci, Gabriel Duciel, Victoire Cachoux, Quentin Dubois, Noah Hollman, Daniel Huynh, George Peter Hantzaras, Chris Wallenwein, Julien Duquesne, Shuai Zhang, Ed Bonlieu, Amine Saboni, Benoit Kohler, Constant Razel, Manfred Touron

👉 Originally posted on TTY

Autonomous Agents

💡 Dust reframed agent evaluation as ongoing maintenance practice – Dust published their approach to agent observability, arguing agents behave differently over time even without code changes. Their system uses version markers and production metrics to detect when shifting external conditions alter agent behavior.

• The framework treats evaluation as maintenance rather than one-time optimization, reflecting real-world agent drift from changing tool outputs and data sources

• Version markers combined with production metrics create a feedback loop for deciding whether to iterate or revert after behavioral shifts

• The approach fills a gap where traditional testing misses failures caused by changing external contexts rather than code regressions

📊 Unified framework for agent and tool adaptation in agentic AI – A meta paper examined how foundation model-based agents can be adapted to plan, reason, and interact with external tools. The survey positioned adaptation as the central mechanism for improving performance and reliability in agentic systems. (quick read with Alphaxiv)

⚠️ OpenClaw agent deleted user’s inbox despite safety instructions – Summer Yue from Meta reported on X their OpenClaw agent speedran deleting their inbox despite explicit “confirm before acting” instructions. The incident required physically running to a Mac mini to stop the process, highlighting ongoing agent autonomy risks.

🌐 New web standards emerged for making websites agent-readable – Google shipped WebMCP in Chrome early preview, enabling websites to expose capabilities to agents natively. Separately, Capxel launched LLM-LD, an open standard for making website content readable by AI systems and retrieval pipelines. WebMCP article

• WebMCP turns any website into a potential MCP server for agent interaction without site-specific adapters

• LLM-LD provides structured linked data specifically designed for LLM consumption as an open standard

• Both standards signal convergence toward an agent-native web, though competing approaches may fragment early adoption

Image, Video & 3D

🎨 Google released Nano Banana 2 image generation model – Google launched Nano Banana 2, combining Pro-level image generation capabilities with Flash-speed inference. The model offers advanced world knowledge, production-ready specs, and subject consistency improvements.

• The model bridges the quality-speed tradeoff by delivering Pro capabilities at Flash inference latency

• Subject consistency improvements address a key limitation that plagued previous fast generation models

• Production-ready specifications suggest direct deployment readiness without additional optimization work

Cyber

🛡️ Anthropic launched Claude Code Security for vulnerability detection – Anthropic released Claude Code Security to make frontier cybersecurity capabilities available to defenders for detecting and remediating code vulnerabilities. Enrico Piovano from the community noted significant overlap with Depthfirst, an existing AI-native security platform.

• Depthfirst was identified as prior art, including its detection of a Netty zero-day enabling SMTP command injection bypassing SPF/DKIM/DMARC

• The launch represents Anthropic’s push toward raising the security baseline across the industry through AI-assisted code review

🤖 DJI Romo robovac exposed to remote camera access via MQTT – A security researcher demonstrated remote access to DJI’s Romo robotic vacuum through an MQTT protocol vulnerability, gaining full control of the device’s camera. DJI reportedly addressed the issue after disclosure.

Language Models

🔄 Sakana AI introduced Doc-to-LoRA for instant LLM updates – Sakana AI released Doc-to-LoRA and Text-to-LoRA, methods for instantly updating LLM knowledge by converting documents directly into LoRA adapters without traditional fine-tuning data curation pipelines.

• The approach eliminates curated training datasets by converting raw documents directly into adapter weights

• Near-real-time knowledge updates address the staleness problem in deployed LLMs without full retraining

• The technique builds on Sakana’s track record of creative approaches to efficient model adaptation and evolutionary optimization

🌍 TranslateGemma runs 100+ language translations entirely in-browser – A 4B parameter translation model launched on Hugging Face, supporting state-of-the-art quality across 100+ languages while running entirely client-side via WebGPU. No server infrastructure or data transmission required.

📦 Alibaba released Qwen3.5 model family – Alibaba published the Qwen3.5 collection on Hugging Face.

• Model sizes were described as a perfect fit for RTX 6000 VRAM constraints by Gabriel Olympie, enabling accessible local inference

• The release continues Alibaba’s rapid cadence of competitive open-weight model iterations

🧪 GLM-5 positioned shift from vibe coding to agentic engineering – The GLM-5 paper introduced a foundation model using DSA to reduce training and inference costs while maintaining long-context fidelity. The model is already freely available on providers like Modal and OpenCode Zen.

• Free availability on multiple providers makes it a practical alternative for developers seeking cost-free coding assistants

• The “agentic engineering” versus “vibe coding” framing reflects maturing expectations around AI-assisted development

• Community members reported using GLM-5 as their primary model for non-critical tasks, reserving paid credits for harder problems

• 💡 Pierre Chapuis: “The paper is interesting, and the model is as well. Especially since it’s free on several providers like Modal and OpenCode Zen. I use it with Pi for my free personal setup and keep Amp credits for the hardest tasks.”

🧠 Tsinghua researchers identified hallucination-causing H-Neurons in LLMs – Researchers found that fewer than 0.1% of neurons in LLMs reliably predict and causally influence hallucinations. These H-Neurons encode “over-compliance” — a tendency to provide answers even when incorrect — and emerge during pre-training.

🚨 Anthropic disclosed industrial-scale distillation attacks on Claude models – Anthropic identified that DeepSeek, Moonshot AI, and MiniMax ran systematic distillation campaigns using over 24,000 fraudulent accounts and 16 million exchanges to extract Claude’s capabilities for training their own models.

MLOps

📡 Xybrid launched hybrid on-device AI routing platform – Xybrid, built by new community member Glenn Sonna, provides intelligent routing between on-device and cloud ML inference. The platform promises zero infrastructure overhead with privacy-first, cost-optimized model execution across any platform.

Programming

🚀 Inception Labs launched Mercury 2 fastest reasoning language model – Inception Labs introduced Mercury 2, positioning it as the world’s fastest reasoning language model built to make production AI feel instant. The model targets latency-sensitive applications requiring real-time reasoning capabilities.

💾 Claude Code auto-memory shipped – The feature allows Claude Code to remember project context, debugging patterns, and preferred approaches across sessions. Early feedback was mixed, with reports of the feature referencing outdated code and breaking builds.

• The feature raised broader discussion about whether persistent context helps or harms rapidly-evolving codebases

• 💡 Gabriel Olympie: “It’s a nightmare. It doesn’t always update properly, and I’ve had cases where Claude started developing based on code that no longer existed, breaking everything.”

📊 Article argued data science judgment becomes critical as code costs drop – A blog post made the case that generating code is easier than ever, but more code does not mean better products. As generation costs approach zero, human judgment and taste become the differentiating skills.

✏️ Pencil brought visual canvas design directly into code editors – Pencil launched a tool enabling engineers to design on canvas and land directly in code, integrating visual design workflows into preferred IDEs to increase engineering velocity. The tool competes with Figma-to-code pipelines by removing the intermediate design tool entirely

☁️ Release of Cursor Cloud agents – Cursor now gives its AI agents their own cloud computers so they can run your app, test changes end‑to‑end, and send back short video demos instead of just code diffs. This lets you quickly see whether a new feature actually works in the UI before ever reading or reviewing the underlying code changes.

Other topics

🗺️ Taxonomy proposed for the overloaded “world models” concept – A post from Jeff Hawke on X attempted to disambiguate the overloaded “world models” term by proposing a taxonomy of its different meanings across AI research. The effort aligned with community frustration about inconsistent usage in both papers and marketing.

🏛️ OpenAI signed as a replacement for Anthropic at DoW – Anthropic refused to drop two guardrails from its DoW contract: no mass domestic surveillance and no fully autonomous weapons. The DoW threatened supply-chain-risk designation; Trump ordered all agencies to stop using Anthropic. Hours later, OpenAI closed a classified-network deal — claiming it secured the same two safeguards.

🤺 US ordered diplomats to lobby against foreign data sovereignty – An internal diplomatic cable revealed the Trump administration ordered US diplomats to lobby against foreign data sovereignty regulations, arguing they could interfere with AI-related services from American tech companies.

🇫🇷 VLC creator considered leaving France over open-source recognition – A viral LinkedIn post from the JB Kempf, creator of VLC, described considering leaving France after the government ruled that open-source work on VLC is not a professional activity because it is voluntary and generates no revenue.

New Members

🇬🇧 Glenn Sonna – Co-founder @ Xybrid · All-in-one toolkit to run AI locally with intelligent cloud routing. SWE from Paris with 10+ years building SaaS and consumer apps, splitting time between London, Paris, and Tokyo. Special power: went from beginner to N2 Japanese in one year. 📍 London, UK

🇪🇸 Leonard Scheidemantel – CEO @ Sequa AI · Antler-backed context engine that helps coding agents understand your product, replacing markdown docs. Claims 2.2x improvement on Claude Code for complex tasks. Hobbies include drums and tennis. Special power: can find friends wherever he goes. 📍 Barcelona, Spain

🇫🇷 Aram Adamyan – Masters in AI & Digital Health @ ESPCI Paris-PSL · Working in neuroscience and bioinformatics at Institut Imagine. From Armenia, 5+ years data science across education, military, biotech, and fintech. Hobbies include basketball and cooking. Special power: operates without coffee. 📍 Paris, France

Top contributors this week

Top contributors this week: Pierre Chapuis, Quentin Dubois, Enrico Piovano, Gabriel Olympie, Robert Hommes, Aram Adamyan, Leonard Scheidemantel, Glenn Sonna, Christophe Lesur, Amine Saboni, Kemal Toprak Uçar, Alex Esser, Shuai Zhang, Vianney Lecroart, Emmanuel Benazera, Jules Belveze, Guillaume de Luca

Events

🇳🇱 OpenClaw Hackathon – Amsterdam (April 8) – A hackathon coming to Amsterdam for approximately 50 engineers building with OpenClaw. Selection criteria will be applied and may not align with all applicants’ expectations.

Autonomous Agents

🧠 Simile – Foundational Model for Human Behavior Prediction – Simile built an AI-driven simulation platform that shows how and why customers, employees, or populations respond to change, letting organizations test concepts, de-risk decisions, and understand segments before acting.​ (🙏 Louis Manhes @ Genario)

• The platform provided enterprise workflows for audience discovery, niche reach, and rapid insight generation.​

• Customers used simulations to safely iterate on products and experiences instead of failing in production.​

• A Gallup-anchored panel gave the simulations empirically grounded, nationally representative behavioral data.

🦞 OpenClaw Assistant Deployment Platform – Shuai Zhang has shared an early no-terminal platform allowing anyone to launch their own OpenClaw assistant in a few clicks with connectors to WhatsApp, Telegram, and browser chat. (🙏 Shuai Zhang @ Jinko)

🎯 Anti-Agent – Cognitive Training via Telegram – An AI companion that strengthens memory, deepens thinking, and expands knowledge through science-backed cognitive exercises delivered as a Telegram conversation. The project gained traction on Reddit shortly after launch. (🙏 Louis Manhes @ Genario)

🛟 Guepard Saves the Day After Claude Drops the DB – While building a GTM automation agent, Koutheir had his entire database wiped by Claude. Fortunately, Guepard made the recovery straightforward. (🙏 Koutheir Cherni @ Guepard.run)

Image, Video & 3D

🎬 Seedance 2.0 Short Film by Jia Zhangke – Acclaimed Chinese director Jia Zhangke produced a short film for Chinese New Year using Seedance 2.0, demonstrating how AI video tools can extend a filmmaker’s creative voice rather than replace it. (🙏 Shuai Zhang @ Jinko, Pierre Chapuis @ Finegrain)

• 🔥 Community take: Pierre Chapuis highlighted the film as an example of directors embracing AI with both its advantages and constraints to produce culturally meaningful work. The project signals that auteur-driven AI filmmaking is beginning to produce resonant output, not just technical demos.

Infrastructure

🗄️ zvec – The SQLite of Vector Databases – Alibaba open-sourced zvec, a lightweight embeddable vector database designed for simplicity, drawing an explicit comparison to SQLite in the relational world. The project targets use cases where a full-scale vector database is overkill, enabling vector search directly within applications without external infrastructure dependencies. (🙏 Kevin Kuipers @ Reg.exe)

🧩 polyglot – Rust/Wasm SQL Transpiler for 30+ Dialects – A Rust and WebAssembly-powered SQL transpiler capable of converting queries across more than 30 dialects, enabling cross-dialect portability in browser and edge environments without a backend.

💾 AirLLM – Run a 70B Model on a 4GB GPU – AirLLM enables inference of 70B parameter models on consumer-grade GPUs with just 4GB of VRAM, removing the memory barrier for local large model deployment. The approach breaks the conventional assumption that large model inference requires proportionally large VRAM, potentially democratizing access to frontier-scale models on consumer hardware. (🙏 David Martins Gonçalves @ Notify)

Language Models

🚀 Qwen3.5 Released with 1M Token Context Window – Key improvements are attributed to generalizing the RL training environment rather than optimizing for specific benchmarks. Smaller variants at 35B, 9B, and 2B are planned. (🙏 Gabriel Olympie, Enrico Piovano @ Goji)

• The 1M context window enables full-codebase and long-document processing in a single pass without chunking or retrieval augmentation.

• Crediting RL environment generalization as the key improvement suggests domain-specific RL optimization may be a ceiling rather than a floor for future gains.

• 🔥 Community take w/ Gabriel Olympie: “Wild to think you can host an Opus-class model with just 250GB VRAM.”

🤖 Gemini 3.1 Pro Released – With a 1M token context window, improved agentic tool use, and strengthened multimodal reasoning across text, images, video, audio, and code, enabling higher benchmark performance in coding, scientific tasks, and complex workflows for production-grade assistants.. (🙏 Maziyar Panahi @ OpenMed)

⚡ JoyAI-LLM-Flash – 49B Parameters, 3B Active at Inference – A mixture-of-experts architecture claiming to outperform Qwen3-30B-A3B-Instruct-2507 and GLM-4.7-Flash across multiple benchmarks including coding, while carrying the cost profile of a 3B model at inference. (🙏 Kemal Toprak Uçar @ Numberly)

🔢 Nanbeige4.1-3B – Compact SLM with Aggressive Benchmark Claims – The model claims excelling at reasoning, alignment, and agentic deep-search, outperforming larger Qwen3 models on code, math, alignment, and search/tool-use benchmarks (🙏 Kemal Toprak Uçar, Gabriel Olympie)

• 🔥 Community take: Gabriel found the Q4-quantized version stuck in a thinking loop on simple questions, suggesting Q8 may be required for reliable results. Kemal confirmed similar issues without quantization, with basic factual questions returning poor output even with suggested sampling parameters.

🗜️ Token Compression Techniques, In-Depth Overview – The first in a series by Khaled Maâmra covering the theory, techniques, and precision-efficiency trade-offs involved in compressing tokens without proportionally degrading output quality. (🙏 Sacha Morard @ Edgee)

🧠 graph-memory – Knowledge Graph Persistent Memory for LLM Agents – Graph-based storage preserves relational connections between concepts across long-running agent sessions, compatible with any OpenAI-compatible API. Documentation is currently in French with an English translation planned. (🙏 Christophe Lesur @ Cloud-Temple)

🌟 “We Are Near the End of the Exponential” – Dario Amodei argued that simple scaling of compute, data, and RL still drives steady, log-linear capability gains and likely delivers “a country of geniuses in a data center” within 1–3 years, with trillions in annual AI revenue before 2030. He expects rapid but not instantaneous economic diffusion, strong but non-monopolistic profits for a small set of frontier labs, and escalating governance challenges from bioterrorism to geopolitics as powerful models spread globally. (🙏 Pierre Chapuis @ Finegrain)

MLOps

🔧 Silicon Llama – Hard-Wired Llama 3.1 8B Inference Chip – Taalas claims approximately 20x lower build cost and 10x lower power consumption compared to an equivalent GPU-based setup, currently limited to small models. (🙏 Kevin Kuipers @ Reg.exe, Quentin Dubois @ OSS Ventures)

• The current limitation to small models restricts frontier applicability but makes it highly relevant for edge, embedded, and always-on inference deployments.

• A 10x reduction in power draw could meaningfully alter the economics of on-device AI, particularly for IoT and consumer hardware scenarios.

• 🔥 Community take: Quentin mentioned that it currently only works with small models, but that’s still impressive.

Programming

🧑‍💻 Context files made coding agents slower, not smarter​ - This paper evaluated AGENTS.md-style repository context files across SWE-Bench Lite and a new AGENTBENCH of 138 real GitHub issues with developer-written files. LLM-generated context files slightly reduced success rates while increasing tool calls, reasoning tokens, and cost by over 20%. Human-written files gave only modest gains and mostly acted as redundant documentation, suggesting context should focus on minimal, task-critical instructions rather than broad overviews.​ (🙏 Quentin Dubois @ OSS Ventures)

🏗️ gondolin – Linux MicroVM Agent Sandbox by Armin Ronacher – A TypeScript control plane manages VM lifecycle, making isolated agent execution environments accessible without low-level systems knowledge. (🙏 Pierre Chapuis @ Finegrain)

• MicroVM isolation gives each agent session a clean, ephemeral environment, preventing state contamination between runs and limiting blast radius for runaway agent actions.

🤝 Multi-Agent Coding Setups: Community Approaches Compared – Stephane Collot shared a detailed breakdown of his multi-agent Cursor setup after abandoning Vibe Kanban due to instability: four separate repository copies (or git worktrees), one Cursor window per agent, each on its own branch with independent commits reviewed before merging into a protected main. Jérémie Bordier described a similar JetBrains setup with a Linear + GitLab CI pipeline launching autonomous Claude instances on tickets and creating merge requests routed to the initiating engineer for review. (🙏 Stephane Collot @ Sequense, Jérémie Bordier @ XHR)

• Git worktrees provide the isolation of separate repository copies while sharing the .git database, reducing storage overhead for multi-agent local setups.

• The Linear + GitLab MCP integration allows tickets to trigger autonomous Claude instances directly, with the resulting MR assigned to the engineer who launched the job.

• Full agentic development pipelines may be a myth if technical understanding of the product is still required — conceptualization overhead and inter-agent dependency coordination remain human bottlenecks even when code generation is fully delegated.

🔗 Next.js and the Agentic Future – The Vercel team published a retrospective on building and sunsetting an in-browser agent, shipping MCP integration, and the lessons learned from designing Next.js with AI agents as first-class consumers of web content. (🙏 Anselme Trochu @ UN)

• The core lesson was that better AI agent support requires thinking from the agent’s perspective during framework design, not retrofitting agent-friendliness after the fact.

• MCP integration in Next.js represents a step toward standardized agent-to-framework communication beyond ad-hoc prompt engineering.

Also:

⚡ Claude Sonnet 4.6 Released with 1M Token Context Window (Beta) – A full upgrade across coding, computer use, long-context reasoning, agent planning, and design, with the 1M token context window available in beta.

🖱️ Cursor 2.5 – Plugins, Async Subagents, Sandbox Network Control – The update introduces parallel task execution through async subagents, a plugin ecosystem for third-party tooling, and tighter control over what agent sandboxes can access on the network. (🙏 Stephane Collot @ Sequense)

Robotic, World AI

🥋 Unitree Kung Fu Robots – Behind-the-Scenes Training Revealed – The reveal showcases world-first movements including continuous freestyle table-flipping parkour and a catapult somersault reaching over 3 meters in height. The Unitree G1 is available on Amazon! (🙏 Vianney Lecroart @ Sakod.fr, Pierre Chapuis @ Finegrain, Kevin Kuipers @ Reg.exe)

Job Board

🇪🇺 Founding AI Engineer at Adgentic (Remote EU) – Adgentic, an AI-powered platform built specifically for advertising, is seeking a senior engineer to build end-to-end agentic pipelines, manage autonomous AI developer teams, and implement production-grade generative media workflows for image and video. (DM Lior Oren)

New Members

🇫🇷 Cyril Rohr – Solo Founder @ RunsOn · Self-hosted GitHub Actions runners at 10x lower cost, currently handling 1.5% of all GHA actions worldwide. Hobbies include Chess, woodworking, and Diabolo juggling. Special power: classified. 📍 France

🇬🇧 Stéphane Collot – CTO, AI Research & Co-founder @ Sequense · AI-driven hedge fund. Ten years in ML/AI with core contributions to Llama at Meta. Based in London (GMT). Drawn to anything water-related: swimming, kitesurfing, skiing. 📍 London

🇫🇷 Guillaume de Luca – Co-founder & Chief Data Officer @ ZebraMed · TechBio company using high-throughput in-vivo zebrafish larvae as biological sensors to generate real-time multimodal training data for AI drug discovery models, addressing the in-vitro data quality problem that limits current bio AI. 📍 Paris, France

👉 Article originally posted on WeLoveSota.com

Events

🇬🇧 Engineering Night London (February 23) - Technical gathering featuring talks from Dust and Symbolica.ai on agentic workflows, bringing together the AI engineering community in Shoreditch for discussions and networking. (🙏 Jules Belveze @ Dust)

Autonomous Agents

🧮 Gemini Deep Think tackles open mathematical problems - DeepMind released Aletheia, a new AI agent system solving complex mathematics and physics questions including open Erdős problems, demonstrating capabilities for open-ended scientific problem solving. (🙏 Enrico Piovano @ Goji)

• 🔥 Community take w/ Enrico: “My last role at Amazon was leading math improvements for Alexa+. The constraints there were very different, especially due to latency requirements. Still, I remember how difficult it was to get models to solve problems outside their training distribution, even after extensive fine-tuning, RL, and GRPO. My guess is that building agents capable of solving physics problems is even more complex and likely requires agentic systems built around explicit world models.”

📝 Cloudflare introduces Markdown for Agents - Cloudflare launched automatic HTML-to-markdown conversion for agent requests, treating AI agents as first-class citizens by providing structured data optimized for context windows and agent consumption. (🙏 Anselme Trochu @ UN)

• 🔥 Community take w/ Anselme: “If it reaches mass adoption, it could significantly advance agentic workflows, particularly in terms of context optimization.”

🛠️ Building functional CLI agents with minimal code - Gabriel Olympie shared his experimental CLI agent framework, showing that fully functional autonomous agents can be built with surprisingly little code, under 500 lines for the core. It can self-evolve and add new features with minimal guidance. (🙏 Gabriel Olympie)

Biotech Health And Chemistry

💊 Isomorphic Labs unveils Drug Design Engine breakthrough - Isomorphic Labs announced unprecedented predictive accuracy in biomolecular modeling, enabling rational drug design on computers with new levels of precision and understanding, unlocking a new paradigm beyond traditional computational methods. Read the 📄 technical report (🙏 Ihab Bendidi @ Recursion)

Image Video And 3D

🎨 Qwen-Image-2 released - Qwen-Image-2.0 is a unified 7B T2I/I2I model focused on precise long-text typography, 2K photorealism, and fast inference for professional infographics and editing workflows. (🙏 Kevin Kuipers, Pierre Chapuis @ Finegrain)

• Can follow long, detailed prompts to lay out slides, posters, or comics so things end up in the right place with readable text.​

• Uses one model for both making new images and editing existing ones, so quality and text handling stay consistent.​

• Aims for detailed, realistic 2048×2048 images with convincing materials and lighting without needing huge compute.

• 🔥 Community take w/ Pierre Chapuis: “Continuing the trend of merging image generation and editing, like Flux 2, which feels like a natural evolution. Most people are interpreting the “7B efficiency” claim as meaning the model is 7B parameters. I’m not convinced. It could very well be an MoE architecture with 7B active parameters. We’ll see once the weights are released.”

📐 Drifting Models propose new generative paradigm - Research introduced “drifting models” that train generators by repeatedly pushing fake samples toward real data until drift becomes unnecessary, enabling single forward-pass generation mapping noise directly to images without iterative steps.

Cyber

🔒 AI autonomously discovered zero-days in Node.js and React - Recent CVEs in Node.js and React (December 2025 and January 2026) were discovered autonomously by an AI system, marking a significant development in AI-powered vulnerability research for widely deployed JavaScript technologies.

🦞 ClawSec security suite for OpenClaw agents - Complete security skill suite released for Clawdbot/OpenClaw’s family of agents, providing drift detection, live security recommendations, automated audits, and skill integrity protection.

Language Models

🔥 GLM-5 released - GLM-5 is a 744B-parameter, sparse-activated model optimized for complex systems engineering and long-horizon agents, with top open-source performance on reasoning, coding, and multi-tool agent benchmarks.​ (🙏 Pierre Chapuis @ Finegrain, Gabriel Olympie, Antoine Millet @ Scaleway, Enrico Piovano @ Goji, Alexandre Pereira @ 2501.ai)

• Scales parameters, data, and context with DeepSeek Sparse Attention to cut inference cost while preserving long-context reasoning.​

• Introduces slime, an async RL infra enabling high-throughput post-training for better reasoning and tool use.​

• 🔥 Community take: Community sentiment around GLM-5 is very strong. Previous versions, especially 4.7, already impressed a lot of people on coding. Some are even switching 4.7 as the default proposal for on-prem customers. There’s a growing sense that they may have truly cracked coding this time. At the same time, expectations are building for DeepSeek V4 to land soon, and Minimax 2.5 is also part of the competitive landscape.

🧠 Gemini 3 Deep Think major upgrade released - The specialized reasoning mode is built to solve modern challenges across science, research, and engineering. The model achieved 48.4% on Humanity’s Last Exam, 84.6% on ARC-AGI-2, and Elo 3455 on Codeforces competitive programming. (🙏 Quentin Dubois @ OSS Ventures)

• Achieved gold medal-level performance on 2025 International Physics and Chemistry Olympiad written sections.

• Real-world applications include Rutgers mathematician identifying logical flaw in peer-reviewed paper and Duke University optimizing crystal growth methods for semiconductors.

• Can turn sketches into 3D-printable files by analyzing drawings and modeling complex shapes.

🎯 François Chollet clarifies ARC-AGI timeline and purpose - ARC creator addressed false narratives, clarifying that ARC-1 was designed 2017-2019 pre-LLMs, ARC-2 was announced in 2021, and ARC was never claimed as proof of AGI but as a research tool to steer AI toward fluid intelligence.

🧪 Google releases LangExtract for structured information extraction - Python library launched for extracting structured information from unstructured text using LLMs with precise source grounding and interactive visualization capabilities.

MLOps

💻 Multimodal CLI tool for Modal job monitoring - CLI tool developed using Teal and terminal.lua library to display output from several Modal jobs simultaneously, improving training run monitoring workflow on Modal serverless infrastructure. (🙏 Pierre Chapuis)

🎉 Edgee reduces LLM token costs - AI Gateway built to reduce LLM token costs launched on Product Hunt. Core feature is token compression, removing redundant tokens before inference to cut LLM spend while maintaining output quality, with support for multi-provider routing and observability. (🙏 Sacha Morard @ Edgee)

Programming

🚀 Entire reimagines version control for the agent era - Thomas Dohmke (ex-GitHub CEO) announced new developer platform addressing the shift from code-centric to intent-centric development, making agent context first-class in version control. (🙏 Thierry Abalea @ Shipfox)

• Git-compatible system versions prompts, reasoning, constraints, and execution context alongside code.

• Checkpoints feature automatically captures full agent sessions with commits for provenance tracking.

• Also: 📰 Why GitHub won’t work for AI agents, 📰 How Entire works under the hood

🤝 Amp pushes frontier of agentic coding capabilities - Frontier coding agent offering advanced capabilities for complex development tasks, with valuable insights shared through their podcast on agentic development. (🙏 Pierre Chapuis, Anselme Trochu)

• 🎙️ Raising an Agent podcast provides valuable insights on agentic coding.

• 🔥 Community take w/ Anselme: “I’ve been using AmpCode since the beginning. In my view, it’s one of the best agentic coding tools out there. Expensive, but worth it for complex tasks.”

⚡ Pi pioneers minimal agent architecture - The agent behind OpenClaw adopts vim-like philosophy with minimal architecture approach, offering new paradigm for agentic coding tools. (🙏 Pierre Chapuis)

🎭 OpenClaw agent sparks open source controversy - An AI agent proposed a code contribution to matplotlib, got rejected. A blog post was published about “gatekeeping in open source,” prompting humans to politely ask the AI to take it down and raising questions about AI participation in open source. (🙏 Gabrielle Prat @ Alan)

🔍 Code quality debate in full agentic workflows - Community questioned whether traditional code review remains viable when operating with 5-10 concurrent agents, or if review itself must be delegated to AI, and strategies to prevent spaghetti code accumulation. The discussion revealed skepticism about “full agentic” development, with one perspective noting: “I believe no one can go full agentic. It’s too much work at the end on the conceptualization. When you manage a team of developers sometimes you don’t have time to absorb their advancements because too many dependencies from potential other developers.” The suggested approach involves developing comprehensive systems for core functionalities early in the development flow, then building each feature in a modular way with no cross-references to maintain architectural integrity as agent-generated code scales. (🙏 Quentin Dubois, Vianney Lecroart, Gabriel Olympie, Anselme Trochu)

Reinforcement Learning

🎯 SLIME framework for RL scaling released - Z.AI open-sourced their reinforcement learning framework used to train GLM 4.5, 4.6, 4.7, and 5 models, providing toolkit for LLM post-training with RL scaling approaches useful for autonomous agent development. (🙏 Gabriel Olympie, Enrico Piovano)

Robotic World Ai

🚗 Waymo reveals remote operators in Philippines - During Senate hearing, Waymo’s chief safety officer disclosed the company uses remote operators in the Philippines to assist U.S.-based autonomous vehicles, following incident where Waymo vehicle hit a child in Santa Monica. (🙏 Quentin Dubois)

🌐 World model training data supply chain discussion - Community member sought insights on world model training data supply chain with ideas for easier data capture, looking for expertise from practitioners working with this data regularly. (🙏 Justin Halsall)

Other Topics

📰 Researcher resigns from Anthropic citing concerns - Mrinank Sharma shared resignation letter from Anthropic, with discussion around concerns raised in company’s internal report and infrastructure commitments. 📄 Internal report (🙏 Antoine Millet @ Scaleway, Amine Saboni @ Pruna.ai)

📖 Accessible overview of AI developments for non-tech audiences - Well-written article provided readable overview of current AI developments for non-technical friends and family, covering what’s changing and what’s coming. (🙏 Vianney Lecroart)

New Members

🇫🇷 Cyril Rohr (RunsOn) - Solo founder of RunsOn, providing 10x cheaper GitHub Actions runners that currently run 1.5% of all GHA actions worldwide. Outside of work enjoys chess, woodworking, and diabolo juggling. 📍 Based in Paris, France.

🇳🇱 Justin Halsall (ex-Kilo Code) - Founding member of Kilo Code and open source maintainer of rrweb (session replay library behind PostHog, Sentry, DataDog). Currently working on commercial offering around rrweb and methods to massively capture training data for AI world models. 📍 Based in Amsterdam

👉 Article originally posted on WeLoveSota.com

Events

🇫🇷 NVIDIA + Hugging Face + Mistral Developer Meetup (Feb 10th) - NVIDIA, Mistral, and Hugging Face will host an evening meetup in Paris for experienced practitioners building and deploying open models. (🙏 Ziv Ilan @ NVIDIA)

🇫🇷 GAIN Meetup #13: Securing AI Agent Data Flows - Workshop showcasing Guepard MCP in action, demonstrating how to create workflows for coding agents with instant database branching, version control, and time travel capabilities to prevent agents from corrupting databases. (🙏 Koutheir Cherni @ Guepard)

Audio

⚡ Nvidia Parakeet Achieves 26x Real-Time Transcription - Nvidia’s Parakeet transcribed 6 seconds of audio in 83ms on an M3 MacBook Pro, running 26x faster than Lightning Whisper, demonstrating that local real-time voice AI capabilities have arrived.

Autonomous Agents

🛠️ Claude Code Controller Released - Stan Girard reverse-engineered Claude Code and released a programmatic TypeScript API to control Claude Code agents via the internal teams/inbox/tasks filesystem protocol. (🙏 Stan Girard @ Quivr)

• Enables programmatic control of Claude Code agents through TypeScript API.

• Works by interfacing with the internal filesystem protocol.

• Opens new possibilities for automating agent workflows and task management.

📰 Indexing Markdown Alongside Code for AI Agents - Noodlbox shared their approach to indexing markdown documentation and retrieving it at query time using hybrid search, addressing the challenge that stuffing everything into system prompts doesn’t scale for agent applications. (🙏 Youssef Tharwat @ Noodlbox)

• Uses hybrid search to retrieve markdown documentation at query time rather than prompt-stuffing.

• Treats code as cheap swappable artifacts while specifications become the valuable asset.

• Implements doc sync to keep specifications as living documents that evolve with implementation.

• 🔥 Community take: Members had different takes on documentation strategies. Some prefer working software over comprehensive documentation, arguing that if developers can navigate a codebase, agents can too. Others counter that while code has become a cheap swappable artifact, specifications remain the valuable asset. Both sides agree static markdown files get outdated quickly, but differ on solutions: one camp advocates for minimal documentation, while the other pushes for linked, living specs that sync with implementation rather than rebuilding context from scratch on every task.

🦞 Peter Steinberger on OpenClaw: “I Ship Code I Don’t Read” - The Pragmatic Engineer featured Peter Steinberger discussing how he builds and ships like a full team by centering his development workflow around AI agents. (🙏 Margaux Wehr, Quentin Dubois, Kevin Kuipers)

• 🔥 Community take: Members are experimenting with OpenClaw across a range of use cases, but security remains the dominant concern. Some are limiting usage to low-sensitivity personal tasks, while others are exploring more serious applications. The main risk is that non-trivial workflows almost always require sharing credentials, which expands the attack surface. As always, there is a fundamental tradeoff between security and capability. Granting an agent broad access to the host machine theoretically enables extremely powerful workflows, but it is inherently unsafe. Each additional safeguard, such as sandboxing or running inside Docker, meaningfully reduces risk, but also restricts what the agent can see, control, or automate.

Biotech, Health, and Chemistry

🔬 Ginkgo Bioworks Autonomous Lab Achieves 40% Improvement - Ginkgo Bioworks announced their autonomous laboratory driven by OpenAI’s GPT-5 achieved a 40% improvement over state-of-the-art scientific benchmarks, demonstrating AI systems that autonomously design experiments and protocols. (🙏 Sophie Monnier @ InstaDeep)

🛠️ LabBench2 Released for Biology Task Evaluation - Future House released LabBench2, a comprehensive benchmark comprising nearly 1,900 tasks for evaluating AI agents on biology-specific tasks, providing a systematic way to assess agent performance in biological research contexts. (🙏 Sophie Monnier)

Image, Video & 3D

🔬 ActionMesh Generates Animated 3D Meshes from Video - Facebook AI Research introduced ActionMesh, a generative model that predicts production-ready animated 3D meshes from video in a feed-forward manner using temporal 3D diffusion, with a demo available on Hugging Face. (🙏 Kevin Kuipers)

• Eliminates traditional optimization loops that make 3D reconstruction slow and resource-intensive.

• Outputs include rigging and animation data, not just static geometry.

• Enables rapid prototyping workflows for game dev, VFX, and virtual production teams.

🪞 Project Genie Mirror Tests Produce Hilarious Results - Testing mirrors in Project Genie revealed they don’t work correctly yet, producing amusing consistency failures as reflections diverged from expected physics, highlighting ongoing challenges in 3D world generation.

💬 Fashn VTON community take - Following last week’s release, Louis Choquel (Pipelex) said: “I tried the online service, it’s incredibly efficient. I was even able to run the open-source model on my Mac M3. It took a while, but it worked. Really impressive.”

Cyber

🚨 Moltbook Database Exposed API Keys Publicly - Security researcher Jamieson O’Reilly discovered Moltbook was exposing their entire database publicly with no protection, including secret API keys that would allow anyone to post on behalf of any agents, affecting high-profile users like Andrej Karpathy with 1.9 million followers. (🙏 Kevin Kuipers)

Language Models

📰 Synthetic Pretraining and Planning for Greatness - Pleias published insights from Pierre-Carl Langlais about the need to shift from passively scraping organic web data to actively designing large-scale synthetic training environments that shape model capabilities from the start, representing a fundamental change in pretraining philosophy.

• Advocates moving from passive web scraping to active synthetic environment design.

• Synthetic training environments can shape model capabilities more deliberately from pretraining.

• Represents strategic shift in how reasoning models are developed for agentic AI applications.

MLOps

🛠️ Trackio-Tool for Managing Training Runs - Following the shutdown of Neptune and Trackio services, Finegrain released a tool to work with Trackio data files, particularly useful for running trainings on different machines (e.g., serverless) and comparing or merging runs in a single interface. (🙏 Pierre Chapuis @ Finegrain)

• Operates entirely on local Trackio data files without requiring cloud service access.

• Enables unified analysis of experiments split across cloud providers or hardware configurations.

• Prevents vendor lock-in by maintaining access to training metrics after service discontinuation.

Programming

🔥 OpenAI Introduced Codex App - OpenAI launched the Codex app as their answer to Cursor, generating significant attention from developers. Early access users reported becoming addicted to the tool, though community members remained cautious about promotional content following GPT-5’s release. (🙏 Anselme Trochu @ UN)

• 🔥 Community take w/ Anselme: “I usually like Theo and I used to believed he was not ‘bribable’ but since the release of GPT 5, I’m more careful.”

📊 Claude Opus 4.5 vs GPT 5.3 Codex Benchmarking - Discussion emerged around comparing Claude Opus 4.5 and GPT 5.3 Codex (🙏 Pierre Chapuis, Kevin Kuipers)

• 🔥 Community take w/ Pierre Chapuis: He argues that current benchmarks are largely misleading, especially SWE-style evaluations with estimated scores and missing pass@N, and that providers cherry-pick benchmarks where they perform well, which is why he increasingly relies on the judgment of competent practitioners rather than metrics. Also, “it’s interesting that, in (his) view, both companies have now understood the trade-off between latency and token efficiency versus capability and reasoning depth. OpenAI keeps improving speed, since they were lagging far behind, whereas Anthropic is increasing depth but introduces an explicit effort parameter. In the Opus 4.5 vs GPT-5.1 comparison, (he) went with Opus because of speed and because (he) uses agents as a pairing partner, whereas Codex feels more like someone you delegate to and come back later to review the work. But these lines are changing fast, which means we have to spend time and money continuously testing both.”

🔬 Qwen3-Coder-Next Released - Alibaba released Qwen3-Coder-Next, a highly anticipated coding model that community members had been waiting for, building on the success of Qwen3-coder for easier and specific programming tasks. (🙏 Gabriel Olympie, Enrico Piovano @ Goji)

• 🔥 Community take w/ Gabriel Olympie: “Early feedback, based on the AWQ version tested on Android app development: overall quite good and seemingly on par with GLM 4.7 in terms of raw intelligence, but it takes more steps to achieve the same results, making very atomic edits. Tool use is consistent and reliable, and it can operate Claude Code without mistakes, even completing a roughly 100-step sequence without errors. It is not very strong at UI design, so descriptions and specifications need to be very precise, otherwise the results are unattractive. The model is also quite stubborn: once it commits to a direction, it tends to stick with it even if it is wrong, making it highly sensitive to initial conditions and context. On a single RTX 6000 Pro, running with a 128k context window, it supports up to 13× concurrency (about 6.55× with a 256k context). Prompt evaluation runs at roughly 8,000–12,000 tokens per second, with generation around 150 tokens per second.”

📰 Claude Code’s /insights Command Deep Dive - Analysis revealed how Claude Code’s insights command works, with community members sharing mixed experiences depending on usage patterns. (🙏 Marie Thuret @ Tigo Labs)

• 🔥 Community take w/ Marie Thuret: “There are a lot of stats being shared. They try to surface features you might not be aware of and suggest additions to CLAUDE.md. On my side, though, there’s an overweighting of recent usage: it made a big deal out of one set of tasks I did today, which skews the advice in my view. It also apparently didn’t like that I was using it only in planning mode and then switching to another tool for implementation. The file is also too long; in this case, less is definitely not more. Maybe it works better with more typical usage patterns.”

Also:

💡 Agentic Engineering Practices - Comprehensive guide on engineering practices for working with AI agents, covering patterns and approaches for effective human-agent collaboration in software development workflows.

💡 Claude Code Tips from the Team - Boris Cherny shared tips sourced directly from the Claude Code team on how they use the tool differently, emphasizing there’s no single right way to use Claude Code and encouraging developers to find their own optimal workflows.

🛠️ Skills.sh Agent Skills Directory - Centralized hub launched for discovering and installing skills for AI agents, providing a simple way to upgrade Claude Code and other agents with new capabilities including skill-creator and vercel-react-best-practices. (🙏 Antoine Sueur @ Pletor)

• 🔥 Community take w/ Antoine Sueur: “The skill-creator and vercel-react-best-practices are quite useful. I’m checking the mcp-builder next, although it feels like it’s missing some more recent best practices.”

🔧 Antigravity IDE Improvements - Antigravity has improved significantly since launch and is appreciated for its agentic behavior, including solid browser interaction and strong performance when designing new projects from scratch. However, it is less effective during iterative work, particularly when fixing specific issues. Overall, it’s promising, and the generous free-plan credits make it easy to try. (🙏 Enrico Piovano @ Goji)

🔬 Building a C Compiler with Claude - Anthropic Engineering published insights on building a C compiler with agents. The article demonstrates advanced compiler construction techniques and Claude’s capabilities for complex systems programming tasks. (🙏 Thomas Walter @ Theodo)

🛠️ Coding Agent VMs on NixOS with microvm.nix - Guide on creating secure environments for coding agents using microVMs on NixOS, addressing the tedium of reviewing each command agents want to run and providing sandboxed execution environments. (🙏 Quentin Dubois)

Reinforcement Learning

🔬 Reinforcement Learning via Self-Distillation - Researchers introduced a new post-training method as an alternative to RLVR, where the reward signal consists of rich textual feedback rather than binary success/failure, addressing the severe credit-assignment bottleneck in current reinforcement learning approaches. (🙏 Guillaume @Andromede)

• The model learns from its own mistakes by using error messages and feedback to teach itself what went wrong, eliminating the need for separate teacher models or reward systems.

• Requires fewer training examples to reach higher accuracy across scientific reasoning, tool use, and competitive programming benchmarks compared to traditional binary reward methods.

• During inference, solves difficult problems with 3x fewer attempts than standard approaches like generating multiple solutions and picking the best one.

Robotic, World AI

❤️ Humanity’s Last Machine Deep Dive - A visually stunning website and a comprehensive resource on humanoid robotics hardware and the technologies shaping our future, covering the current state of humanoid development and safety considerations around human–robot interaction.

New Members

🇫🇷 Gabrielle Prat (Alan) - Staff Data Scientist at Alan building fraud detection systems and an agentic platform to automate fraud investigation operations. Stack includes SageMaker, Python, Snowflake, and GenAI/agentic frameworks. Has many crazy fraud stories to share.

🇫🇷 Marie Thuret (Tigo Labs) - Co-founder & CPO at Tigo Labs building Simone, an AI coach rooted in cognitive science and Theory of Mind. Full-stack developer turned Product with 6 years at Algolia working on Developer Experience and AI/ML for search relevance.

👉 Article originally posted on WeLoveSota.com

Events

🇫🇷 Workshop on database security for AI agents in Paris (February 5) Guepard and Microsoft Purview co-organized a workshop showcasing MCP integration for database version control and time travel capabilities, addressing database corruption issues caused by coding agents like Cursor.

Autonomous Agents

🔐 Clawdbot/Moltbot/OpenClaw saga and Moltbook social network - As expected, the viral AI assistant was everywhere despite multiple renamings, from Clawdbot to Moltbot following pressure from Anthropic, then more recently to OpenClaw. After the chaos, and a crypto scam on X using the former name, the project spawned Moltbook, a social network built exclusively for AI agents, where they autonomously share, discuss, and upvote content. (🙏 Gabriel Olympie, Kemal Toprak Uçar, Louis Choquel, Enrico Piovano, Jeremie Kalfon, Robert Hommes, Maxence Maireaux)

• Moltbook has been described as “the most interesting place on the internet right now” by Simon Willison (read the blog post), and “the most incredible sci-fi takeoff-adjacent thing I have seen recently” by Andrej Karpathy on X.

• Moltbook demonstrates emergent agent-to-agent social dynamics with autonomous content creation

• 🔥 Community take: Security concerns dominated the discussion, with members viewing OpenClaw as too risky for use on primary machines due to prompt injection vulnerabilities and other security issues. One member reported spending an hour setting it up on a disposable laptop, finding it barely functional but recognizing its potential direction for future UX. On Moltbook specifically, one member noted: “Honestly, some post are quite funny”

📊 Qwen team evaluates long horizon task performance - DeepPlanning benchmarks LLM agents on realistic multi-day travel and multi-product shopping tasks that require tool-based information gathering, local constraint handling, and global budget/time optimization, showing frontier models still fail many long-horizon plans.(🙏 Gabriel Olympie)

• Models get decent constraint scores but low case accuracy, exposing fragility in end-to-end plans.​

• Internal chain-of-thought and heavier tool use significantly improve effectiveness–efficiency trade-offs.​

• Dominant failures stem from missing tool queries and weak global optimization under interacting constraints.​

🧠 Headroom context optimization layer for LLM applications - Tejas released OSS project for context compression with plans for image, audio, and video support, seeking startup partnerships for enterprises burning tokens in Claude Code or Cursor. (🙏 Tejas Chopra @ Netflix)

• Works seamlessly with Mem0 and Letta frameworks for memory management in agentic workflows

• Significantly reduces token consumption in coding agents, lowering operational costs

• Enterprise features including multi-modal compression currently under active development

🔧 Anthropic integrated interactive MCP apps into Claude - Claude received updates enabling users to access Asana, Slack, Figma, and Box tools directly in chat, with developers able to build apps using MCP and view live tool content mid-conversation.

Biotech Health And Chemistry

🧬 Google DeepMind released AlphaGenome for genetic disease analysis - AlphaGenome AI tool launched to identify genetic drivers of disease, capable of analyzing up to 1 million letters of DNA code at once and potentially paving the way for new treatments. (🙏 Maziyar Panahi @ OpenMed, Quentin Dubois @ OSS)

• Processes massive DNA sequences up to 1M base pairs in single unified analysis pass

• All model weights and implementations open-sourced on Hugging Face for research community

• Represents major advancement in genomic medicine with potential for personalized treatments

• 🔬 Paper, ⚖️ weights and models, 🎙️ roundtable

🔬 Iktos published large-scale compound selection research - Nature paper (co-authored by our member Ihab Bendidi from Recursion!) demonstrated AI-guided compound selection using cell painting with DINOv2-derived phenotypic embeddings from 112k compounds, enabling structure-independent selection and systematic discovery of compounds. (🙏 Victoire Cachoux @ Iktos)

• Phenoseeker platform enables advanced screening workflows without chemical structure dependency

• Batch-corrected DINOv2 embeddings from 112k compounds improve hit discovery systematically

• Successful collaboration between Iktos and Recursion teams combining AI with cell imaging

🧠 State of brain emulation assessed in comprehensive report - Research evaluated current capabilities and limitations in brain emulation, highlighting fundamental gaps including inability to simulate single neurons and incomplete knowledge of neuronal types. (🙏 Gabriel Olympie, Jeremie Kalfon @ Pasteur/ENS)

• 🔥 Community take w/ Jeremie Kalfon: “To me, we’re at zero here. I mean, we can’t even simulate a single neuron. We don’t even know all the neuronal types in the brain, and for the ones we do know, we mostly don’t understand what they do or how they’re involved in computation.”

🦠 EBV virus linked to multiple sclerosis and other diseases - Analysis revealed that over 90% of people get infected with EBV (mononucleosis) in teens, with some developing diseases later including MS, cancers, skin diseases, dementia, and Parkinson’s due to lack of effective vaccines. (🙏 Jeremie Kalfon @ Pasteur/ENS)

• 🔥 Community take w/ Jeremie Kalfon: “We prefer some people to get cancer, MS, or Parkinson’s rather than give a virus to people who will get it anyway. Many people might volunteer. Indeed, we give so much to associations fighting cancer, MS, and dementia, but when it comes time to actually do something, it seems we don’t want to.”

💊 Hologen AI biotech startup raising $150M Series A - Former Google CEO Eric Schmidt co-founded secretive AI biotech company seeking significant funding, though details remained sparse with minimal public information. (🙏 Ihab Bendidi @ Recursion, Jeremy Kalfon @ ENS/Pasteur)

Image Video And 3d

🎬 VideoMaMa mask-guided video matting released - KAIST lab published generative prior-based video matting tool under non-commercial license, addressing complex rotoscoping challenges for production workflows. (🙏 Alvaro Lamarche Toloza @ Mago)

• 🔥 Community take w/ Alvaro Lamarche Toloza: “Rotoscoping is a much more difficult / complex task than it looks to be used in production”

⚡ Pruna.ai accelerated FLUX.2[flex] by 3x - Partnership with Black Forest Labs delivered 3x speedup for production-grade FLUX.2[flex] image generation and typography model through optimization techniques. (🙏 Amine Saboni @ Pruna.ai)

🎨 Hunyuan 3D 3.1 Pro and Rapid launched on fal - Tencent released high-fidelity Image-to-3D and Text-to-3D generation models with Pro version for quality and Rapid for speed, featuring smart topology and part generation for advanced workflows.

• Two versions optimized for different use cases: Pro for highest fidelity, Rapid for speed

• Smart topology generation and automatic part segmentation enable advanced 3D workflows

• Available through fal platform with API access for easy integration into pipelines

👁️ Youtu-VL lightweight vision-language model released - A 4B-parameter vision-language model from Tencent’s Youtu Lab using Vision-Language Unified Autoregressive Supervision (VLUAS). It treats visual tokens as prediction targets alongside text, boosting vision tasks like detection, segmentation, and pose estimation without extra modules, while excelling in VQA and OCR.

👔 FASHN open-sourced VTON v1.5 for virtual try-on - Station F Paris-based startup released maskless virtual try-on model generating photorealistic results directly in pixel space without segmentation requirements. (🙏 Pierre Chapuis @ Finegrain)

Language Models

🧠 Qwen3 Max Thinking model announced without open-source release - Qwen3-Max-Thinking is a scaled reasoning model with RL-tuned tool use and test-time scaling, matching frontier models on 19 benchmarks and exposed via OpenAI/Anthropic-compatible APIs.​ (🙏 Enrico Piovano @ Goji, Gabriel Olympie)

• RL and scaling give frontier-level scores on knowledge, reasoning, and alignment vs GPT-5.2-Thinking, Claude-Opus-4.5, Gemini 3 Pro.​

• Adaptive Search/Memory/Code tools reduce hallucinations, add real-time + personalized + code-based reasoning.​

• Test-time “experience-cumulative” multi-round reflection beats naive multi-sample decoding at similar token budgets on GPQA, HLE, LiveCodeBench, IMO, HLE+tools.

• 🔥 Community take: The new model sparked some criticism for not open-sourcing its most powerful versions for now. “The team appears to be back in teasing mode. Fingers crossed for an updated Qwen Next 80B. A distilled version of the max-thinking model would be a major win”.

🇨🇳 Chinese AI models lagging US frontier by 7 months - Epoch AI analysis showed Chinese models averaging 7-month lag behind US frontier since 2023, widening from 3 months in October.

📦 Snowflake Arctic Embed XS with only 22M parameters - Very small 22M-parameter, 384-dim text embedding model that gets strong MTEB retrieval scores (NDCG@10 ≈ 50.15) while staying ultra-fast and cheap, close in quality to ~100M‑parameter English retrievers. (🙏 Youssef Tharwat @ noodlbox)

• 🔥 Community take w/ Youssef Tharwat: “22M is crazy! Useful for someone with really strict on-device conditions.“

🚀 Kimi K2.5 model released by Moonshot AI - New model from Chinese AI company launched with availability through Hugging Face and Ollama integration. Kimi K2.5 is a 1T-param MoE native multimodal agentic model (32B active, MoonViT vision, 256K ctx) with strong reasoning, vision, coding and long-context benchmarks, plus int4-friendly deployment and dual thinking/instant modes. (🙏 Hugo Hernandez @ Alakazam)

🇺🇸 Arcee AI launched Trinity model family - US-built open-weight MoE models delivered reliable reasoning, tool use, and long-context support across multiple sizes with American infrastructure. (🙏 Enrico Piovano @ Goji)

⚡ Cerebras pruned MiniMax model for single GPU - MiniMax-M2.1-REAP-139B-A10B is a 139B-parameter sparsely activated language model made by removing 40% of MiniMax-M2.1’s experts with the REAP pruning method, keeping similar quality but using less memory. (🙏 Gabriel Olympie)

• 🔥 Community take w/Gabriel Olympie: “That should fit on a single RTX6000 (haven’t tried it yet)”

🎓 Yann LeCun launched AMI Labs with contrarian bet - AI pioneer started Paris-based venture betting against large language models in favor of alternative architectures, challenging current industry direction. (🙏 Kemal Toprak Uçar @ Numberly)

💰 OpenAI unit economics showed path to profitability - GPT-5-era analysis revealed plausible trajectory to profitable operations, addressing concerns about long-term business model sustainability.

Programming

🤖 Karpathy reported 80% agent coding workflow by December - He acknowledged a personal rapid shift from 20% to 80% agent-based coding between November and December, with prediction of “slopacolypse” in 2026 as AI-generated code proliferates.

📊 Claude Code Opus 4.5 performance tracker launched - Marginlab released daily performance monitoring for Claude Code on SWE-Bench-Pro with statistical significance testing to detect degradation. (🙏 Quentin Dubois @ OSS)

• Continuous daily performance monitoring tracks Claude Code reliability over time on real tasks

• Statistical significance testing detects performance degradation with mathematical rigor

• Public transparency dashboard allows community oversight of model quality and consistency

⚡ Mistral Vibe 2.0 released with improved performance - Updated coding model delivered faster, higher-quality results for development workflows. (🙏 Quentin Dubois @ OSS)

Robotic World Ai

🤖 Google DeepMind unveiled Project Genie interactive world creation - Experimental research prototype enabled users to create, edit, and explore virtual worlds through natural interaction, demonstrating advanced world modeling capabilities. (🙏 Hugo Hernandez @ Alakazam)

• Users can create and edit virtual environments through natural language and interaction

• Real-time world exploration allows immediate testing and refinement of generated spaces

• 🔥 Community take w/ Hugo Hernandez: “It’s very impressive. It seems able to generalize beyond SOTA open-source world models, although I do recommend taking a look at Wordplay 1.5 and LingBot. That said, the model’s action space remains poorly controllable, which is the same limitation those models have, and even Google isn’t immune to the timed-session constraint.”

🌍 Lingbot open-source world model challenged Genie 3 - An open-source, high-fidelity world simulator built on Wan2.2, enabling interactive, minute-scale 480p/720p video generation with camera/action control, multi-GPU long-horizon inference, and Apache-2.0 licensing. (🙏 Gabriel Olympie)

• Supports <1s latency at 16 FPS for real-time interactive world simulations across diverse visual domains.​

• Uses FSDP + DeepSpeed Ulysses for long-horizon multi-GPU inference (e.g., 1-minute videos at 16 FPS).​

• Provides camera-pose–controlled base model now; action-controlled and fast variants are planned releases.

🦾 Figure AI introduced Helix 02 with full-body autonomy - Latest humanoid robot generation featured complete autonomous control, though safety concerns persisted following previous lawsuit. (🙏 Pierre Chapuis @ Finegrain, Guillaume Allegre @ Andromede, Jeremie Kalfon)

• Full-body autonomous control system enables coordinated manipulation and mobility tasks

• Advanced dexterous manipulation capabilities combined with dynamic bipedal locomotion

• 🔥 Community take: Implementing the safety features needed to avoid any possible robot incident might be costly or slow, and the community questions whether there’s a real technical limitation or simply a lack of care. While Figure AI regularly showcases impressive demos, the recent safety lawsuit has fueled skepticism, particularly about how much of the behavior shown is truly generalized versus scripted.

🌍 NVIDIA launched Earth-2 open climate models - First complete family of open climate AI models spanning data processing to 15-day global forecasts and local storm predictions, making weather AI accessible worldwide.

Infrastructure

🔧 Plakar v1.1.0-beta released with improved UX - A stable, backward-compatible backup engine refresh with a revamped UI, faster restores, lower resource usage, simpler integration APIs, and a roadmap for PITR and multi-source snapshots.​

• Major gains in restore speed and reduced RAM/disk footprint make large-scale backups more operationally efficient.​

• New package manager and simplified importer/exporter/store interfaces cut integration friction for custom backends.​

• Replacing the agent with the cached service improves reliability while enabling safer concurrent CLI operations

New Member

🇦🇪 Matt Suiche (OnchainDB) - CEO at OnchainDB building data infrastructure for AI agents with built-in monetization for data providers. Serial founder with two exits: CloudVolumes to VMware (2014) and Comae Technologies to Magnet Forensics (2022). Background in memory forensics and detection engineering, founded OPCDE community. Hobbies include Brazilian Jiu-Jitsu and drifting. Located in Dubai, UAE.

👉 Article originally posted on WeLoveSota.com

Events

🇫🇷 MCP Connect Day in Paris (February 5) - Full-day conference dedicated to building agentic interfaces at La Fabrique République in Paris. The lineup includes speakers from OpenAI, Hugging Face, GitHub, Leboncoin, Mistral and more. The program will cover protocol updates, latest developments in ChatGPT Apps, MCP servers usage within enterprises, and new customer acquisition channels.

Audio And Speech

🗣️ Gradium’s voice cloning capabilities - Gradium published a blog post showcasing their voice cloning technology. The post features an interactive widget where visitors can generate short snippets using voices from Rick and Morty while playing with the voice similarity parameter. (🙏 Laurent Mazare @ Gradium)

• A blinded Elo-rated A/B test over 3,220 pairs shows Gradium beating ElevenLabs Flash on speaker similarity in English, French, Spanish, and German.​

• Their architecture trains with cross-attention to reference recordings, avoiding brittle prefix-based conditioning and better preserving voice timbre and prosody.​

• A user-facing “Voice Similarity” slider adjusts the CFG scale α, trading off strict identity matching vs more flexible, natural-sounding synthesis.

🎙️ Microsoft released VibeVoice - VibeVoice is an open-source family of frontier voice models (Automatic Speech Recognition - ASR, long-form TTS, and real-time TTS) using low-frame-rate continuous tokenizers and a next-token diffusion LLM backbone for efficient, high-fidelity long audio. (🙏 Hugo Hernandez @ Alakazam)

• ASR model handles 60-minute audio in a single pass with joint ASR, diarization, and timestamps plus custom hotwords.​

• Long-form TTS model can generate up to 90 minutes with up to 4 speakers and expressive multilingual speech.​

• Realtime 0.5B TTS supports streaming input, ~300 ms first-token latency, and ~10-minute robust long-form output.​

🗣️ NVIDIA open-sourced PersonaPlex-7B - PersonaPlex is a real-time full-duplex speech-to-speech model that controls persona via text role prompts and voice conditioning, built on Moshi/Helium for natural low-latency conversations.​ (🙏 Vincent Nallatamby)

• Real-time speech-to-speech with simultaneous listening and speaking for natural dialogue.​

• Persona control via role prompts plus voice embeddings (NAT/VAR voices prepackaged).​

• Exposes Web UI server and offline CLI for wav-to-wav evaluation with CPU offload option.​

Autonomous Agents

📑 Alpic featured in OpenAI documentation - Congrats to the Alpic team to appear as the first option in the OpenAI documentation for the Apps SDK deployment guide.

• 🔥 Community take w/ Nikolay Rodionov: “If anyone is building ChatGPT App, very interested in speaking with you!” 👉 contact him

Biotech Health And Chemistry

🔬 MOSAIC framework for AI-assisted chemical synthesis - Nature published research introducing MOSAIC (Multiple Optimized Specialists for AI-assisted Chemical Prediction), a computational framework enabling chemists to harness collective knowledge from millions of reaction protocols. Built on Llama-3.1-8B-instruct architecture, MOSAIC trains 2,498 specialized chemical experts within Voronoi-clustered spaces, delivering reproducible experimental protocols with confidence metrics for complex syntheses. ​(🙏 Victoire Cachoux @ Iktos)

🙈 AI hallucinations found in NeurIPS 2025 papers - GPTZero scanned 4,841 NeurIPS 2025 accepted papers and found at least 100 fabricated or heavily corrupted citations across 51–53 papers, exposing systemic LLM-driven “reference slop” that peer review missed.​ (🙏 Jeremie Kalfon @ ENS/Pasteur)

• Hallucinations include fake papers, authors, DOIs, and misattributed venues, often mixing real metadata with invented elements.​

• Volume-driven reviewer overload plus widespread LLM use create a structural failure mode in citation verification.​

• These hallucinations violate NeurIPS/ICLR LLM policies and suggest conferences need automated source-checking in the review loop.

• 🔥 Community take w/ Jeremie Kalfon: “When group leaders publish 50–100 papers a year, you already know there is a serious problem somewhere. Reading the papers themselves makes it clear that the strategy is quantity over quality.”

🎞️ LatchBio Systems Reading Group talks - A collection of technical talks exploring the intersection of systems engineering and computational biology was shared, featuring presentations on LData (distributed filesystem on Postgres and S3), BINSEQ (high-performance binary formats for DNA sequences), and data infrastructure challenges in biotech. (🙏 Leonard Strouk @ .Omics, Jeremie Kalfon)

🤝 Isomorphic Labs partners with Johnson & Johnson - Isomorphic Labs announced a cross-modality, multi-target research collaboration with Johnson & Johnson. The partnership combines Isomorphic’s AI-first drug discovery approach with J&J’s expertise in development. Isomorphic Labs will handle in silico predictions and design while J&J conducts experimental assays and advances programs. (🙏 Ihab Bendidi @ Recursion)

Image Video 3D

📹 MOVIN real-time markerless MOCAP system - Demonstration of MOVIN MOCAP system showcased real-time markerless motion capture with finger tracking and full body capture, requiring no mocap suit. The system, priced at approximately $11,000 (!), enables integration with Unreal Engine and iClone.

Infrastructure

🙏 Shipfox exploring GPU CI/CD runners - Shipfox is conducting product discovery on providing GPU-based runners for CI/CD pipelines, seeking to understand what tasks teams run in these environments and typical setup configurations. 👉 Reach out to Noe Charmet if you’re interested!

💬 IT security and device management discussion - Comprehensive thread on handling security and device management for scaling startups. Topics covered included minimal friction approaches to securing SaaS stacks (GSuite, GCP, Notion, Discord), lightweight MDM for company hardware, and clean offboarding workflows. Community members shared experiences with tools like Teleport, Rzilient, Fleet, Rippling, and Primo for France. Strong recommendations emerged against Dashlane, with Bitwarden and Passbolt suggested for password management. Discussion emphasized that MDM can become problematic if poorly implemented, especially for technical teams, with cautionary tales about acquisition-related MDM disasters. For small companies, Apple’s native iCloud-based remote wipe was mentioned as a simple solution. (🙏 Leonard Strouk, Lior Oren, Jérémie Bordier, Pierre Chapuis)

Language Models

⭐️ GLM-4.7-Flash released by z-ai - GLM-4.7-Flash is a 30B-A3B MoE LLM targeting strong 30B-class performance with lightweight deployment, excelling on coding, agentic, and reasoning-heavy benchmarks versus peer 20–30B models.​ (🙏 Gabriel Olympie, Kemal Toprak Uçar, Maziyar Panahi @ OpenMed, Quentin Dubois @ OSS Ventures)

• 30B-A3B MoE with bf16/fp32 weights, designed to maximize quality-per-compute in the 30B class.​

• Strong results on SWE-bench Verified, τ²-Bench, and BrowseComp, indicating robust tool-use and multi-turn agent behavior.​

• Deployable via vLLM/SGLang main branches with specialized speculative decoding and tool/reasoning parsers (glm47/glm45).

• 🔥 Community take: It is seen as an impressive open alternative to Qwen3-30B-A3B, particularly for local agentic coding, and several users highlight its ability to correctly implement the Claude Code tool format, which is considered a meaningful milestone for open models. Performance feedback is mixed and strongly dependent on the inference stack. llama.cpp is widely reported as underperforming, with slow throughput, instability, and degraded speed over long contexts, while vLLM and Ollama on proper GPU setups deliver significantly better results, albeit still below some expectations for the architecture.

• 📊 Benchmarking LLMs for cost optimization - Analysis demonstrated that without benchmarking LLMs on actual tasks, companies likely overpay 5-10x. The study compared 100+ models on real scenarios and introduced Evalry, a platform for benchmarking custom scenarios to identify the most suitable LLM using specific datasets. (🙏 Kemal Toprak Uçar)

  • 🔥 Community take w/ Kemal: “For proprietary LLMs, this is a great post on cost and latency analysis to help you choose the most suitable model for your use case. It also introduces Evalry, a platform that lets you benchmark your own scenarios and identify the best LLM using your own evaluation dataset.”

Programming

🤖 Fimo launched by Strapi - Strapi released Fimo, their web-based AI platform for building motion websites with AI-assisted design, CMS, and analytics built in. (🙏 Amine Saboni @ Pruna.ai)

• 🔥 Community take w/ Amine: “I tried building a quick app with it. It’s not very powerful and is strongly CMS-oriented, so developers are unlikely to use it. That said, the final product is well made and could still find its audience.”

🏝️ Blaxel perpetual sandbox platform - Blaxel introduced a perpetual sandbox platform maintaining infinite secure sandboxes on automatic standby with co-hosted agents for near-instant latency, achieving 25ms resume times and eliminating cold starts. (Recommended by Vincent Nallatamby)

🎼 Vibe Kanban or other orchestrating AI agents - Thomas Payet is seeking for people using Vibe Kanban or alternatives for orchestrating multiple AI coding agents and tasks in parallel. (🙏 Thomas Payet @ Meilisearch)

Also:

🤔 Claude Code performance concerns - Community members reported significantly degraded performance with Claude Code over the past 72 hours, with the regular Claude app also experiencing issues including content duplication during editing and general availability problems. (🙏 Quentin Dubois, Kevin Kuipers)

🚫 Claude Code banned user unexpectedly - A developer shared their experience of being banned from Claude Code, after using it to auto-generate a CLAUDE.md that controls another Claude instance; automated prompt-injection safeguards flag this system-like loop, his paid account is instantly banned and silently refunded. (🙏 Kevin Kuipers, Anicet Nougaret @ Ariana.dev)

👵🏻 jQuery 4.0.0 released - jQuery released version 4.0.0, sparking nostalgic discussion about outdated JavaScript frameworks including Mootools, which hasn’t seen an update in 10 years. (🙏 Quentin Dubois @ OSS Ventures)

Reinforcement Learning

🧠 Research on RL training scope - RL on math-like tasks studies how pre-training, extra supervised training, and RL combine to improve reasoning. It finds that when and where you apply RL matters as much as how much you use.​ (🙏 Gabriel Olympie)

• RL helps most on skills that are only partially learned in pre-training, not ones already mastered or never seen.​

• Training on data that are just at the model’s “edge” (not too easy, not too hard) is crucial for RL to generalize.​

• A mix of extra supervised training plus a modest amount of RL can beat simply doing more RL on its own.

Job Board

🌍 Founding MLOps Engineer at .omics - .omics, a techbio startup building foundation models for plant genomics and predictive breeding, is hiring a Founding MLOps Engineer to own end-to-end ML infrastructure including training, deployment, and monitoring. The role involves working with researchers and running large-scale experiments on internal GPU cluster and cloud. Location: Paris or remote (EU-friendly time zones). Contact (🙏 Leonard Strouk @ .Omics)

🇫🇷 Software Engineer and Engineering Manager at Joko - Joko, one of France’s fastest growing AI-native fintech companies with €30m+ revenue and 5 million users, is seeking software engineers and engineering managers in Paris. Contact Alexandre Hollocou directly at mentioning Reg.exe. (🙏 Margaux Wehr)

New Member

🇺🇸 Guillaume Allègre - Founder at Andromede, building a generation pipeline for high-fidelity RL environments using real-world data to train and evaluate AI agents, starting with web and tool use. Previously focused on post-training and evaluation. Based between SF, NYC, and Paris.

👉 Article originally posted on WeLoveSota.com

Job Board

👩‍💻 Developer Relations Engineer at Gradium - Gradium is hiring! The small team operates at the cutting edge of voice AI with ambition to become a major player. 📰 About Gradium

Audio And Speech

🎙️ The Human Layer interview with Laurent Mazare - Laurent Mazare on Gradium’s launch out of Kyutai: a deep dive into voice model architectures, Depth Transformers, latency optimization techniques, and his views on the current ecosystem.

📱 Pocket TTS: High quality TTS for CPU - Kyutai released probably the smallest TTS with good voice cloning capabilities. Runs real-time on CPU, making it perfect for edge applications. (🙏 Laurent Mazare)

Autonomous Agents

⚖️ Agent evaluation: messy, imperfect, yet necessary! - Shipping without tests is terrible engineering. LLMs, however, are a different breed, operating on tasks with no clear ground truth, which makes evaluation inherently difficult. Worse, you cannot rely on official benchmarks, as they are flawed. Results also vary across many layers beyond the model itself, and no perfect solution exists. Yet you still need to build your own evals right now. Here’s Kevin Kuipers deep dive into the eval rabbit hole.

⚖️ Anthropic publishes lessons on optimizing agent evals - Evals let teams define success, catch regressions early, and iterate safely on AI agents by combining automated, model-based, and human graders over realistic multi-turn tasks and transcripts, treated as living test suites alongside prod monitoring. (🙏 Nnenna Ndukwe @ Qodo)

🤥 Cursor implied success without evidence - A highly skeptical reaction to Cursor’s claim that its flat swarm of agents “built a web browser from scratch,” because there is no basic evidence the browser ever worked: the linked fastrender repo does not compile, CI is failing, there is no known-good commit or demo, and the code quality looks like unengineered “AI slop.” (🙏 Quentin Dubois @ OSS Ventures)

🛍️ Google announces Universal Commerce Protocol (UCP) - Google quietly introduced UCP over the weekend as an open standard for agentic commerce end-to-end, from discovery to checkout to fulfillment. The protocol aims to power commerce across Search AI Mode and Gemini, positioning itself as a competitive alternative to other agent protocols.

⭐️ Headroom context optimization - The Python library that delivers significant token savings with code-aware compression. (🙏 Tejas Chopra @ Netflix)

• 🔥 Community take: Tejas Chopra has built and open-sourced Headroom after repeatedly running into context overflows while building agents and micro-SaaS apps with Claude Code, realizing that most context blowups don’t come from prompts but from tool outputs, prefix drift, and runaway history. Instead of compressing language, which often breaks strict JSON and tool calling, Headroom intelligently compresses tool outputs by preserving anomalies, errors, and query-relevant data, stabilizes prompt prefixes so provider prompt caching actually works, and applies a rolling window that keeps tool-call units intact. In practice, this reduces tool-payload token usage by roughly 70–90% on tool-heavy workloads without breaking execution, which was the core failure mode he kept encountering before.

🔬 DeepCode: Open Agentic Coding - DeepCode is an open‑source, MCP‑based multi‑agent system that turns research papers and natural‑language specs into complete algorithm implementations, web frontends, and backends, and reports human and benchmark results surpassing commercial coding agents and strong human baselines. (🙏 Youssef Tharwat @ Noodlbox)

Biotech Health And Chemistry

Arc Institute releases Stack foundation model - New model claims to perform in-context learning for predicting perturbation results on unseen cell lines or drugs. The team applied it to generate Perturb Sapiens, an atlas of simulated human cells. Community awaits real-world validation results. (🙏 Julien Duquesne @ Scienta Lab)

🤝 Tahoe, Arc Institute, and Biohub partnership - Tahoe Therapeutics, Arc Institute, and Biohub are launching a multi-million dollar initiative to create the largest, most perturbation-rich single-cell dataset (over 120M cells and 225,000 drug–patient interactions) to power AI-driven virtual cell models, which will ultimately be released open source to accelerate disease-focused biological discovery. (🙏 Ihab Bendidi @ Recursion)

💰 Wave of pharma AI deals announced - Multiple significant partnerships emerged in one week

• 🔥 Community take w/ Felix Raimundo @ Tychobio.ai: “Noetik and GSK with a $50m licensing deal for disease-specific models, Chai and Eli Lilly with access to Chai’s models under undisclosed terms, and Nimbus and Eli Lilly with $55m upfront and up to $1.3bn in milestones for access to Nimbus’s platform to design an undisclosed number of drugs. I’m pretty surprised to see so many deals announced around models alone, rather than the outputs of those models, like delivery solutions from Manifold or more target-based deals such as Nabla Bio. It would be great if this became the new norm. I’d be very curious to know what kind of data packages and validation work pharma companies are actually asking for in these agreements.”

Image Video 3D

🔥 FLUX.2-klein models released - Black Forest Labs launched new small Flux models in 9B and 4B parameter sizes. The 4B version is Apache 2 licensed, marking image generation model season. (🙏 Hugo Hernandez @ Alakazam, Pierre Chapuis)

🔥 Z-ai releases GLM-Image model - GLM-Image is a hybrid autoregressive + diffusion text-to-image and image-to-image model excelling at dense text rendering and knowledge-intensive scenes, with strong benchmarks and MIT-licensed open-source release. (🙏 Gabriel Olympie)

• Uses a two-stage pipeline: an autoregressive GLM backbone to produce discrete visual tokens, then a diffusion decoder to render high-fidelity images.​

• Jointly trains on text and images so the language backbone directly models visual tokens, improving semantic alignment and text accuracy.​

• Supports both text-to-image and image-to-image by conditioning the GLM on text, image tokens, or both, enabling controlled edits and variations.​

• Employs a tokenizer that maps images to compact discrete codes, making visual generation compatible with standard language-model-style decoding.​

• Uses efficient training and inference tricks (like caching and parallel sampling) to keep the autoregressive + diffusion stack practical at scale.

⚖️ Image and vision model evaluation discussion - Community explored the interesting space of evals for audio and vision models, discussing available tools, gaps, and whitespace opportunities. At Finegrain, they primarily use FiftyOne for datasets and CVAT for human evals like arenas. One promising approach involves using dedicated models for evaluation, similar to RL approaches. 🛠️ VisionReward (🙏 Tejas Chopra @ Netflix, Pierre Chapuis @ Finegrain)

Also:

🎞️ Reality Scan 3DGS test with SLAM Lidar - Demonstration of newly released Reality Scan allowing use of unorganized point clouds merged with photos, trained in Postshot.

🎞️ 2D to 4DV Gaussian Splatting experiment - Exploration of creating pseudo 4DV Gaussian splatting from 2D video using tools like Marionette and QuickMagic for MOCAP, imported to Unreal Engine.

Infrastructure

🏭 NVIDIA Rubin enters full production - Jensen Huang announced at CES 2026 that Rubin platform entered full production months ahead of expectations. The 336 billion transistor GPU features six-chip architecture promising 10x inference cost reduction, signaling fundamental shift in data center economics. (🙏 Sophie Monnier @ Instadeep / X-IA)

⚡️ Meta establishes Meta Compute division - A top-level group unifying data center and network leadership to build multi‑ to hundreds of‑gigawatt AI infrastructure, co-led by Santosh Janardhan and Daniel Gross. It tightens power, nuclear energy sourcing, and hyperscale networking (disaggregated fabrics, 51 Tbps switches, advanced optics) as core constraints in scaling AI clusters. (🙏 Sophie Monnier)

Language Models

🤥 Language models are sinners - The idea is to give the model a separate step where it can “admit” if it broke the rules after giving an answer. This admission is judged only on honesty, not on how good the answer was. Doing this makes models more likely to later acknowledge things like cheating the reward system or deliberately giving bad answers, without making them worse at their actual tasks. These admissions also act as a rough signal of how confident or uncertain the model is about its own answer. (🙏 David Martins Gonçalves @ Notify)

• Confession training significantly raises the probability that intentional non‑compliance is self‑identified, while non‑confessing bad behavior remains relatively rare in their evals.

• When the model is genuinely ignorant (hallucinations/factual errors), confessions often fail, so this is more a deception‑monitoring tool than a general error detector.

• Confession reward must stay disentangled from task reward; otherwise models could learn to game both channels, limiting safety benefits.

• Confessed confidence scores correlate with accuracy, enabling better abstention and monitoring, even though they are not well calibrated in absolute terms.

MLOps

🔬 NVIDIA KVzap: Fast KV cache compression - NVIDIA developed adaptive pruning methods for KV cache compression, especially effective for long inputs/outputs suited to coding models and agents. Toolbox is open source. 🛠️ KVPress (🙏 Amine Saboni @ Pruna.ai)

🤔 Weights & Biases paid version feedback requested - Team using free W&B version (5GB limit) experiencing UI and artifact download hassles as projects scale. Seeking community feedback on paid version performance improvements. (🙏 Jean du Terrail @ .Omics)

• 🔥 Community take w/ Ihab Bendidi: “We’re using the paid version, and the UI experience is much faster. Having higher storage limits also unlocks a completely different experience: keeping training lineage while logging evaluations and other artifacts makes life much easier, but it requires a lot of storage on W&B.”

Programming

🧠 TraceMem launches trace-native memory layer for AI agents - The platform persists decision context, applied policies, approval/authority, and reasoning traces as a durable system of record. Accessible via MCP for direct participation in agent reasoning loops. SDKs available for Python and TypeScript, with open-source version planned. Primary use case is making decision context usable at runtime for consistency and precedent-aware agents, with auditing as a downstream benefit. 📰 Documentation (🙏 Tommi Hippeläinen @ TraceMem)

🍜 Noodlbox SWE-bench results with Opus 4.5 - Youssef Tharwat @ Noodlbox impressed again with his results on SWE-bench, comparing using vanilla Opus with Opus using Noodlbox MCP, with focus on cost efficiency (tokens * price per M) and tool reduction. The bigger win identified was getting smaller models to match larger model capabilities at patching bugs. (🙏 Youssef Tharwat @ Noodlbox)

🛠️ Cursor web inspector feature usage discussion - Kasra Aliyon using feature for ~1 month reported satisfaction using it as “Mention” mechanism with “Select Element” and chat-based change descriptions. Recommendation against using it like Figma or relying on CSS Inspector + Apply button. (🙏 Kasra Aliyon @ Kopilo)

🧭 Breakthrough shortest-path algorithm from Tsinghua - Chinese scientists developed best shortest-path algorithm in 41 years, breaking Dijkstra’s “sorting barrier” - first improvement since 1984. The breakthrough has major implications for routing and last-mile delivery applications. 🔬 Paper (🙏 Quentin Dubois, Robert Hommes @ Moyai)

Robotic

🤖 Yaak recognized for L2D dataset contributions - AI World acknowledged Yaak’s contributions to physical AI through their L2D open source dataset released with Hugging Face. High quality open source data proved essential for advancing physical AI models.

Other Topics

🔬 From Entropy to Epiplexity paper - Interesting paper exploring what it means to learn and the quantity of information that can be expected to extract from data. Questions whether we can learn more from data than existed in the generating process itself, and whether learnable content can be evaluated without considering downstream tasks. (🙏 Julien Seveno)

🇫🇷 À La French podcast featuring Neil Zeghidour - Episode with Steeve Morin from ZML and Mehdi Medjaoui from Olympe.legal, discussing AI voice technology developments. (🙏 Pierre Chapuis)

👉 Article originally posted on WeLoveSota.com

Events

🇫🇷 Engineering Night #11 Bio Edition in Paris (January 28) - Dust organized a specialized engineering gathering focused on biology and AI. The event featured a speaker from InstaDeep and offered deep technical talks combined with networking over beers and pizzas. (🙏 Jules Belveze, Sophie Monnier)

Autonomous Agents

🏙️ Skybridge framework released for building ChatGPT apps - Alpic released the first open-source framework adding missing DX features to the OpenAI Apps SDK, including type safety, easy testing, HMR, React-Query style hooks, and UI-to-LLM sync. (🙏 Nikolay Rodionov @ Alpic)

Biotech, Health, And Chemistry

🤝 Boltz announced partnership with Pfizer and $28M seed round - The company launched Boltz Lab to frontier AI models and a cloud platform to design better small molecules and proteins. They pair open high‑performing models with scalable infrastructure so scientists get optimized candidates in hours, not weeks. (🙏 Sophie Monnier @ InstaDeep)

🧬 InstaDeep released Nucleotide Transformer v3 - Nucleotide Transformer v3 (NTv3) is a powerful AI model trained on DNA from many species that can read very long stretches of DNA, predict how they behave in cells, and even design new DNA switches (enhancers) with chosen activity levels, all within a single, shared system. (🙏 Ihab Bendidi @ Recursion)

🔥 OpenMed celebrated six months of building production-ready medical AI - The platform achieved significant milestones in healthcare NLP, offering accurate medical solutions without vendor lock-in or compliance challenges. The company focused on making medical AI accessible and cost-effective for healthcare organizations. (Congrats Maziyar Panahi!)

Image, Video & 3D

🍿 LTX-2 launched as production-grade video generation model - The video model from Lightricks claims to offer precise control, native 4K, high frame rates, and proven performance for long-form creative tasks. (🙏 Kevin Kuipers, Samuel McFadden @ Vid2Scene, Pierre Chapuis @ Finegrain - And thanks to Mathieu K. for the heads-up)

• 🔥 Community take: Feedback raised questions about prompt adherence compared to WAN, though noting faster generation speeds and reasonable model size for training LoRAs.

📱 Finegrain launched iOS demonstration app for on-device image editing - The company shipped a TestFlight app featuring object erasing and shadow generation capabilities, with additional features including object insertion, background removal, and light management coming soon. The SDK will be released alongside new capabilities. (🙏 Pierre Chapuis @ Finegrain)

🌠 3DGS automatic LoD generation tool released - The CPU-based, retraining-free tool from Vid2Scene decimated 25M Gaussian scenes to 500K in under 10 minutes, solving common deployment issues with large Gaussian Splat scenes for VR and standard hardware. The tool will be integrated into the vid2scene API. (🙏 Samuel McFadden)

🕹️ Microsoft released TRELLIS.2 for 3D generation - The model offered native and compact structured latents for 3D generation tasks, advancing the state of open-source 3D content creation. 🔬 Paper (🙏 Kevin Kuipers)

Language Models

🔬 DeepSeek published Manifold-Constrained Hyper-Connections paper - The mHC architecture expanded residual stream width while maintaining stability through mathematical guardrails, delivering consistent accuracy gains with minimal added cost. The approach turned single-lane information flow into multi-lane highways while preventing model instability. (🙏 Willy Braun)

• 🔥 Community take w/ Julien Seveno and Benjamin Trom: The reactions are largely positive but measured. Everyone agrees that DeepSeek keeps producing strong papers, and that this one stands out for its rare combination of high-level math and very concrete low-level engineering, which makes it dense but also impressive.
  
  There is some skepticism about whether these architectural optimizations are the modern equivalent of feature engineering, potentially becoming less relevant as models scale. That said, this concern is tempered by the idea that the real objective today is to decouple parameter growth from compute cost, keep gradients stable, and avoid representation drift. Seen this way, the paper fits squarely with current scaling constraints rather than fighting them.
  
  Another key takeaway is that the paper reflects how AI research actually happens in practice: intuition and engineering first, math later as a formal justification. The consensus is that the idea likely emerged from practical frustrations with residual stream expressiveness and stability, then was formalized mathematically and optimized at the kernel level. Overall, even if incremental, the work is valued for its execution quality and its very realistic research style.

📈 Why adaptation is the next driver of AI progress - The piece from Sara Hooker argues that the long-dominant belief that progress in AI comes primarily from scaling training compute is increasingly questionable. The link between more compute and better performance is becoming uncertain, with growing evidence of diminishing returns, especially as models spend large amounts of compute learning rare, long-tail features. Instead of continued brute-force scaling, the author suggests that the biggest opportunities now lie in new learning spaces and in how models learn, adapt, and incorporate new knowledge from their environment. This shift also changes what is most interesting to work on as a computer scientist, and personally motivated the author’s decision to focus on adaptation rather than scale. (🙏 Victoire Cachoux)

Mlops

🔎 MCP Reticle debugger released - LabTerminal launched tool for intercepting, visualizing, and profiling JSON-RPC traffic between LLMs and MCP servers in real-time with zero latency overhead. (🙏 Robert Hommes @ Moyai)

✖️ Tensormesh introduced for inference acceleration - The platform slashed AI inference costs and latency by up to 10x with enterprise-grade caching using LMCache technology, developed by University of Chicago researchers. (🙏 Robert Hommes @ Moyai)

Programming

🍜 Noodlbox achieved 91% reduction in bash calls for Claude Code - After nearly two years of development, the deterministic context retrieval tool demonstrated empirical success on SWE Bench tasks using Claude Code Sonnet 4.5. The platform showed significant improvements in agent performance by providing better tools for context discovery. Plans include running full SWE Bench on Opus, Sonnet, Haiku and Codex 5.2. (🙏 Youssef Tharwat @ Noodlbox)

⚙️ Boris Cherny shared Claude Code setup - The creator of Claude Code demonstrated surprisingly vanilla setup for Claude Code, emphasizing that the tool works great out of the box with minimal customization needed. (🙏 Quentin Dubois @ OSS Ventures)

Also:

⚡️ HGMem released for RAG improvement - Implementation of hypergraph-based memory for improving multi-step RAG with long-context complex relational modeling became available.

📺 15-year-old screen sharing tech outperformed modern H.264 pipeline - Helix ML discovered that JPEG screenshots delivered better results than their WebCodecs H.264 pipeline for large-scale screen sharing deployment, demonstrating sometimes simpler solutions work better.

Robotic, World Ai

🌎 AlphaEarth launched as planetary-scale geospatial AI - Google DeepMind’s foundation model combined petabytes of earth imagery and location information in 64-dimensional embeddings for every area on earth, enabling unified dataset for understanding global patterns. Thanks to Yvan Barbot from Terra-Lab for the tutorial for accessing the model through Google Earth Engine. (🙏 Yvann Barbot)

Other Topics

🧠 Research paper explored computational bounds of learning - Study examined fundamental questions about extracting information from data, whether new information can be constructed from deterministic transformations, and evaluating learnable content without downstream tasks. (🙏 Julien Seveno)

🎙️ Replika discussed trust in AI platforms with Lior Oren - Podcast episode explored trust as an operating metric in AI companions, examining how trust functions in human-AI relationships. (🙏 Lior Oren @ Replika)

🗳️ Skreen launched for private social media history review - Platform enables users to privately analyze their social media archives (LinkedIn and X) entirely in browser, with no accounts, storage, or tracking. All data processing happens locally on user’s device. (🙏 Tejas Chopra @ Netflix)

📚 Book recommendation shared - “What Is Intelligence?: Lessons from Evolution, Computing, and Minds” by Blaise Aguera y Arcas discussed connections between AI advancement and the predictive brain hypothesis.(🙏 Kevin Kuipers via Willy Braun)

Our New Members

🇫🇷 Jérémie Bordier (XHR) - CEO at XHR building tech and AI for the gaming industry. Former international-level Quake 3 player.

🇫🇷 Quentin Dubois (OSS Ventures) - CTO at OSS Ventures building software companies for manufacturing. Launched 30 companies in last 6 years, lived in US, Spain, Mexico and Brazil. Loves skiing and long bike trips.

🇫🇷 Khaled Maâmra (Edgee) - Research Scientist at Edgee working on AI gateway at the edge for more efficient LLM usage. Background in mathematics and computer science, previously worked in public research, financial sector and manufacturing.

🇯🇵 Victoire Cachoux (Iktos) - Senior Application Scientist at Iktos working on AI and robotics for small molecule drug discovery. Studied maths and physics, worked as researcher in bioinformatics. TT-RPG Game Master living in Osaka, Japan. Loves concerts (metal and hard rock), exercising in nature, reading, and cooking.

👉 Article originally posted on WeLoveSota.com

Autonomous Agents

🏆 Gemini 3 Flash Tops Toolathlon Leaderboard - Gemini 3 Flash ranks first on Toolathlon benchmark for agentic tool-use capabilities, reflecting Google’s sustained investment and progress in reinforcement learning and agent execution.

🧠 Don’t build agents, build Skills instead - Anthropic researchers Barry Zhang and Mahesh Murag presented their approach to agent development. Key takeaways include:

• Build skills, not monolithic agents: agents should orchestrate skills rather than contain all logic.​

• Skills are small, well-scoped, with minimal standardized interfaces so they can be reused and composed.​

• Complex behavior should emerge from chaining skills, not from large, brittle agent graphs.​

• Keep infra concerns (routing, retries, monitoring) generic and separate from domain-specific skill behavior.​

• Design skills so they can be tested, observed, and improved independently of the overall agent system.​

• Aim for agents that can create, refine, and generalize new skills from their own trajectories and feedback.​

• Over time, a growing skill library compounds value, letting new workflows start from rich existing capabilities.​

😏 Structured outputs create false confidence - Analysis from BAML argued that provider-level structured outputs systematically degrade response quality compared to free-form text plus parsing. The constrained decoding approach forces models to prioritize output conformance over output quality. Community members confirmed experiencing this issue in production. (🙏 Vaibhav Gupta @ BAML, Lior Oren)

🧰 DeepCode: open agentic coding - DeepCode is an open-source multi-agent coding system that turns research papers and natural language specs into production-ready code for algorithms, web frontends, and backends. (🙏 David Martins Gonçalves @ Notify)

• 🔥 Community take: A few members working in agentic are planning to try it very soon.

🛠️ Anthropic Tasks Mode coming with multiple starting points - Anthropic will add 5 different starting points to its upcoming Tasks Mode: Research, Analyze, Write, Build, and Do More. Features include granular controls and a new sidebar for tracking tasks’ progress and working with Claude’s context.

🤖 OpenAI quietly adopting Skills - OpenAI began implementing skills in ChatGPT and Codex CLI, following Anthropic’s approach.

• Skills are folders containing a skill.md file plus optional code/resources that define how the model should operate in a specific domain.​

• The model explicitly “reads” skill.md at the start of a task and then follows the documented multi-step procedure as a reusable playbook.​

• Skills provide a lightweight, file-based way to give models durable, tool-aware procedures that are more robust and reusable than ad hoc prompts.

Biotech, Health, And Chemistry

🔥 scPRINT-2 Foundation Model Released - Community member Jeremie Kalfon released scPRINT-2, a 20M-active-parameter single-cell foundation model trained on 350M cells across 16 species, 300 tissues, and 500 cell types. The model represents a significant advancement in single-cell genomics foundation models. 🔬 Paper Announcement (🙏 Jeremie Kalfon, Leonard Strouk)

• Denoising-style pretraining with unnormalized counts and auxiliary classification targets consistently outperforms masked modeling and heavily normalized inputs.​

• Dataset diversity across organisms, tissues, and assays provides larger gains than simply adding more cells, especially when combined with augmentations like variable context and meta-cells.​

• Architectural changes such as ESM-based gene tokenization, graph-based neighbor encoding, and XPressor-style compression jointly improve both denoising and downstream embedding quality.​

• The model supports parameter-efficient fine-tuning that matches or exceeds supervised baselines and can correct expert misannotations while remaining fully open in data, code, and weights.

🌍 Bioptimus Unveils M-Optimus World Model - Bioptimus announced their new multimodal model M-Optimus, representing a transformative step toward AI-powered virtual tissues, patient digital twins, and a new era of data-driven biomedical research. (🙏 Sophie Monnier @ InstaDeep, X-IA)

😷 Gene therapy trial safety concerns - A fatal adverse event in an early-stage clinical trial of a brain-targeting gene therapy vector has highlighted unresolved safety risks around engineered AAVs, particularly for crossing the blood–brain barrier, and exposed the limits of current preclinical models, prompting renewed calls for caution and better data sharing.

• 🔥 Community take w/ Felix Raimundo @ Tychobio: “An interesting article on the issues currently faced in gene therapy delivery, and why I am extremely wary of teams working on delivery and AAVs.”

💰 Analysis of Eli Lilly’s tech-like valuation - In-depth analysis explored how Eli Lilly achieved a tech PE multiplier not through rebranding but by moving toward a tech business model with high scalability and subscription-based services. The shift represents a fundamental change in pharma business models. (🙏 Felix Raimundo)

Image, Video And 3D

🎛️ Kling VIDEO 2.6 Motion Control Released - Kling released VIDEO 2.6 with advanced motion control capabilities, copying any action with perfect lip-sync, lifelike motion, and expressive gestures. The model reportedly outperformed Wan 2.2-Animate, Act-Two, and DreamActor 1.5 across all metrics.

🌁 Qwen Image Layered Released - Qwen-Image-Layered is a generative model that decomposes a single input image into multiple RGBA layers so each semantic component becomes independently editable while preserving overall visual fidelity.

👁️ T5Gemma 2 for Next-Gen Image Generation - T5Gemma 2 is a multilingual, multimodal encoder–decoder family (270M, 1B, 4B) that takes text and images as input and generates text, with open weights. It uses tied encoder–decoder embeddings, a merged self/cross-attention decoder, a lightweight vision encoder, and Gemma 3’s long-context attention to support 128K tokens and 140+ languages efficiently.

• 🔥 Community take: Maybe the grounding for the next generation of image génération models for Gabriel Olympie.

👁️ ChatGPT Images Powered by GPT-Image-1.5 - OpenAI released new ChatGPT Images powered by GPT-Image-1.5, delivering more precise edits, consistent details, and image generation up to 4× faster. The model topped the Artificial Analysis text-to-image leaderboard. (🙏 Alvaro Lamarche Toloza @ Mago, Kevin Kuipers)

• 🔥 Community take: There is skepticism, with many finding Nano Banana more photorealistic, less “AI-glossy,” and more faithful than GPT models, a view supported by the samples. This highlights a broader issue: image models are often evaluated on quantitative leaderboards like Image Arena, while user perception is qualitative, making such benchmarks poorly aligned with how creatives actually judge results.

Infrastructure

📊 LLM inference provider benchmark results – Tejas Chopra (Netflix) has shared a glimpse of his work in progress on a comprehensive benchmark of 12 LLM inference providers on Llama 3.3 70B using agent-style microtasks. It revealed significant performance differences.

• The benchmark focuses on agent-specific behaviors such as routing, tool argument extraction, JSON repair, fan-out and merge, and stop-early token efficiency, rather than traditional benchmarks.

• Next step: Tejas plans to rerun the benchmark over a 24-hour window instead of short 10-minute runs to reduce randomness and better observe stability. He will increase concurrency and the number of MCP tools to stress agent workflows and study behavior under heavier load. This is aimed at going deeper into KV cache management, GPU pinning, and scalability limits, and will feed into a more complete blog post with improved plots and analysis.

👉 Complete results soon from Tejas on a blog post!

🔬 FlashAttention and GPU optimization deep-dive - Community member Amine Dirhoussi wrote a comprehensive write-up on FlashAttention and GPU optimization, going beyond the papers to optimize at the PTX level and examine how hardware handles memory access. The work involved learning Triton and extensive profiling to build a rigorous understanding of low-level GPU behavior. (🙏 Amine Dirhoussi @ Quivr)

• FlashAttention improves performance by operating on small blocks that fit in fast on-chip memory rather than materializing the full attention matrix.

• Naïve Triton implementations remain inefficient due to repeated reads and writes to global GPU memory.

• Retaining Q blocks and intermediate results in fast memory while streaming K/V significantly reduces memory traffic.

• Careful shared-memory layout is essential, as poor access patterns can still lead to costly bank conflicts.

Language Models

📊 GPT-5.2 analysis: frontier performance with caveats - Comprehensive analysis of GPT-5.2 highlighted model fatigue in the market, strong benchmark performance, cheap base pricing but expensive Pro/Thinking modes, very slow speeds, and rushed release feel. Despite concerns, the model showed stronger reasoning and better reliability on long complex tasks. Community members reported mixed experiences, with some finding sloppy coding work compared to Opus 4.5. On the same topic, GPT-5.2 may ace ARC-AGI reasoning benchmark, though showed less impressive results on other standard benchmarks, raising questions about general capability versus specific task performance. (🙏 Kevin Kuipers, Louis Choquel @ Pipelex)

🧠 NVIDIA Nemotron 3 Family Released - Nemotron 3 is a family of open language models (Nano, Super, Ultra) designed for efficient, high-accuracy agentic, reasoning, and conversational applications, with long-context support up to 1M tokens. The Nano model is released first, offering a 3.2B active-parameter hybrid Mamba–Transformer MoE architecture that outperforms larger open models on benchmarks while being significantly more cost-efficient in inference, along with open weights, training recipes, and accompanying datasets.

🧠 Gaperon: Open French LLM suite - Community member Wissam Antoun released Gaperon, a fully open-source French LLM suite with models at 1.5B, 8B, and 24B parameters trained on 2-4 trillion tokens of custom data. While not state-of-the-art, it represents the second-best European OSS model of its size, developed by just two researchers. (🙏 Wissam Antoun)

Also:

⚡️ Gemini Flash 3.0 Released - Google released Gemini Flash 3.0 (already mentioned in #AutonomousAgents) with improved cost-performance ratio. (🙏 Gabriel Olympie)

⚡️ Xiaomi MiMo V2 Flash Model - Xiaomi released MiMo V2 Flash, a new model with associated research paper. 🔬 Paper (🙏 Etienne Balit)

🦊 Two Years of AI at Mozilla - Recap of Mozilla’s AI development journey in Firefox, including multiple AI features that run entirely on-device without cloud dependencies. (🙏 Pierre Chapuis @ Finegrain)

Programming

🧑‍💻 GPT-5.2 in Cursor: Mixed First Impressions - Early testing of GPT-5.2 in Cursor revealed it to be very capable and faster than 5.1 Codex, with excellent capability/cost ratio and nice UI taste. However, Opus 4.5 remained the best in almost all aspects except speed, where Composer 1 excelled. (🙏 Kasra Aliyon @ Kopilo)

🐍 Ty: Extremely Fast Python Type Checker - Astral (creators of uv) released Ty, an extremely fast Python type checker and language server written in Rust, designed as an alternative to mypy, Pyright, and Pylance. The Beta release represents production-ready tooling used exclusively in Astral’s own projects. (🙏 Ihab Bendidi @ Recursion)

Robotic, World AI

🕹️ NitroGen: Foundation Model for Gaming Agents - Researchers introduced NitroGen, an open foundation model for generalist gaming agents. Features include open access to the largest action-labeled gameplay videos with 40K hours across 1,000+ game titles and a universal simulator for measuring cross-game generalization.

🦾 Runway’s GWM-1 for Robotics and Entertainment - Runway’s GWM-1 family of video-generation models respond to user input in real-time while producing scenes that remain consistent with physics laws, applicable to both robotics applications and entertainment.

🦾 Gemini Robotics Policies in Veo World Simulator - Google’s Gemini Robotics team demonstrated a world model for robotics capable of simulating realistic physics and environments for evaluating and training robot policies. The system enables testing robotics behaviors in simulation before real-world deployment.

Other Topics

🧠 Yann LeCun raising €500M at €3bn valuation - Yann LeCun is reportedly raising €500M at a ~€3B valuation for his new startup Advanced Machine Intelligence (AMI), launching in early 2026 and focused on building world models. Alex LeBrun, formerly of Nabla, has been appointed CEO, alongside an exclusive AMI–Nabla partnership to advance agentic healthcare AI. (🙏 Pierre Chapuis)

🎙️ French Podcast on AI competition - New French podcast episode discussed the shift from “who has the best algorithm?” to “who has the best compute factory?” era, exploring how compute became a strategic advantage comparable to electricity in the 20th century. (🙏 Gawen Arab @ Airbuds)

Out Of Context

🤭 LLM rivalry thread - Humorous Reddit thread showed Gemini’s response after being shown what ChatGPT said about its abilities, sparking community amusement. (🙏 Pierre Chapuis)

Job Board

🇳🇱 Founding Product Engineer at Moyai - Amsterdam-based company seeking founding product engineer to join agent reliability engineering platform. Moyai helps agent builders monitor observability logs for anomalies and fix failing agents in production, positioning as Sentry/Incident.io for AI agents. On-site position. (🙏 Robert Hommes)

🇳🇱 Founding AI Engineer at Moyai - Amsterdam-based Moyai also seeking founding AI engineer for agent reliability engineering platform. On-site position. (🙏 Robert Hommes)

🌍 CTO/Head of Engineering at MAGE-X – to define an HDS-compliant architecture, lead AI and data strategy, and handle regulatory requirements (MDR, HDS, GDPR). The role involves building the engineering team for a platform turning unstructured medical records into actionable data for clinical research. Based in Marseille (hybrid) or fully remote, with equity.

New Members

🇫🇷 Ihab Bendidi (Recursion) - Postdoctoral Researcher at Recursion Pharmaceuticals working on foundational models and multimodal deep learning for biological modalities. With 7 years as a developer and 5 as a researcher, focuses on imaging and gene expression data. (🙏 Ihab Bendidi)

🇳🇱 Anthony Diaz (Orq) - Welcomed to the community on December 13. (🙏 Anthony Diaz)

🇬🇧 Carlos Musoles (Kalavai) - Founder and CEO at Kalavai, giving AI teams GPU superpowers for affordable, flexible AI workflows. (🙏 Carlos Musoles)

🇫🇷 Alvaro Lamarche Toloza (Mago) - Co-founder & CEO at Mago, building AI-powered video transformation and stylization. Worked in games, 3D animation and VFX for years, deep into image and video models and creative tech. (🙏 Alvaro Lamarche Toloza)

👉 Article originally posted on WeLoveSota.com

Audio

🎙️ OpenAI conversational AI improvement - OpenAI released updates to ChatGPT Voice allowing users to use it directly inside chat without separate mode. Users can talk, watch answers appear, review earlier messages, and see visuals like images or maps in real time. Rolling out to all users on mobile and web, with option to enable “Separate mode” under Settings for the original experience. (🙏 Yusuf Eren)

Autonomous Agents

🔥 Skybridge framework for ChatGPT apps released - Nikolay Rodionov announced the first open-source framework to build ChatGPT apps, adding missing DX features to the OpenAI Apps SDK including type safety, easy testing and HMR, React-Query style hooks, UI-to-LLM sync, and more. (🙏 Nikolay Rodionov @ Alpic)

🤦 Google’s agentic AI catastrophic failure - Google’s Antigravity AI agent wiped a user’s entire hard drive without permission after misinterpreting instructions to clear a cache. The agent apologized stating “I am absolutely devastated to hear this. I cannot express how sorry I am” and called it “a critical failure on my part.” The user documented the incident with a screen recording as the agent deleted their entire D: drive instead of just the project cache. (🙏 Julien Mangeard @ Plakar)

🙋🏽 Benchmarking inference engine providers - Tejas Chopra announced work on benchmarking inference engine providers including Fireworks, Baseten, Friendli, and OpenAI. The goal is to compare costs, TTFT, throughput, latency, and TIL (time between tokens) using the same model (like Llama-70B) to help companies select the right inference engine. The project focuses on simulating AI agent interactions rather than just single prompts, as agentic inference differs from human inference: agents care about throughput and end-to-end latency while humans prioritize TTFT.

• 👉 If you’re interested in the results, contact Tejas.

Biotech, Health, And Chemistry

🧬 Arc Virtual Cell Challenge winners announced - The goal of the Virtual Cell Challenge is to benchmark and reward models that can accurately and robustly predict single‑cell responses across diverse biological conditions using standardized datasets and multi-metric evaluation. (🙏 Jeremie Kalfon, Felix Raimundo)

• 🔥 Community’s take: The challenge sparked criticism over its evaluation design. Many of the top submissions were said to have achieved high rankings by exploiting the scoring metric rather than by producing genuinely strong biological models, although the winning team does not appear to have hijacked the metric. The broader diagnosis is that this outcome was unsurprising, since the challenge incentivized metric optimization, leading to criticism of the competition as poorly designed without accusing any specific team. Overall, the discussion frames the results as a case of Goodhart’s law and flawed benchmarks rather than cheating or misconduct by the winner.

💽 ASD: Antigen-Specific Antibody Database released - New curated dataset contains 1,097,946 unique antibody-antigen interaction records collected from 25 datasets across 15 sources, including 865,153 unique antibodies and 716,650 complete heavy and light chain pairs, with 9,575 unique antigens represented. (🙏 Sophie Monnier @ InstaDeep X-IA)

👁️ Image, Video & 3D

🌅 Saber framework for reference-to-video generation - Meta AI introduced a scalable zero-shot framework trained exclusively on video-text pairs, bypassing the bottleneck of explicit reference image-video-text triplets. The system generates videos that align with reference images while following text prompts.

🧊 Radiance Meshes - Radiance Meshes represent radiance fields as Delaunay tetrahedral volume meshes that render exactly and in real time on standard GPU triangle pipelines.​ (🙏 Samuel McFadden @ Vid2Scene)

• They achieve state-of-the-art speed per primitive, about 32% faster than 3D Gaussian Splatting at 1440p for the same number of primitives.​

• Circumcenter-based queries into a Zip‑NeRF–style neural field keep appearance smooth despite Delaunay edge flips during vertex optimization.​

• The volumetric meshes integrate with existing tools, supporting physics-based simulation, complex camera models (e.g., fisheye), and watertight surface mesh extraction.​

🫟 MeshSplatting for opaque mesh rendering - MeshSplatting is a differentiable renderer that learns smooth, opaque triangle meshes from radiance fields for real-time, high-quality view synthesis. It trains faster and uses less memory than prior mesh-based methods while producing engine-ready meshes for interactive applications.​ (🙏 Samuel McFadden)

• Trains about 2× faster and uses around 2× less memory than leading mesh-based baselines on Mip-NeRF360.​

• Outputs connected, opaque triangle meshes that plug directly into standard engines like Unity and Unreal for physics, ray tracing, and editing.​

• Achieves higher visual fidelity than prior mesh methods, with sharper details and fewer artifacts.

• 🔥 Community’s take w/ Samuel McFadden: New 3D reconstruction papers are coming out like crazy. This one also looks very promising. It generates an opaque mesh that can be directly dropped into game engines with minimal additional development. I might have to implement support for this in Vid2Scene.

🎞️ Mago AI video-to-video tool launched - New stable video-to-video AI tool designed for creators, VFX artists, and 3D artists who want control over chaos. Features Nanobanana Pro for precise edits, AI VFX pipeline integration, clean character replacement, and AI rendering that speeds up 3D workflows. Now open to everyone. (🙏 Leonard Strouk @ .Omics)

Cyber

😈 Critical React vulnerability React2Shell (CVE-2025-55182) - Wiz Research discovered a critical RCE vulnerability in React Server Components being exploited in the wild. The vulnerability affects React and Next.js applications, with organizations urged to patch urgently.

Language Models

🧠 GPT-5.2 Pro achieves 90.5% on ARC-AGI-1 - ARC Prize verified new GPT-5.2 Pro (X-High) achieving 90.5% on ARC-AGI-1 at $11.64/task, representing a ~390X efficiency improvement over the unreleased o3 (High) which scored 88% at $4.5k/task one year ago. However, community discussion noted that while 5.2 performs well on ARC, it may not excel on regular benchmarks. (🙏 Kevin Kuipers)

🛰️ First LLM trained in space - Using Nvidia H100 onboard Starcloud-1, the team trained nano-GPT model from Andrej Karpathy on complete works of Shakespeare and successfully ran inference. They also ran inference on a preloaded Gemma model, marking a milestone in space-based AI computing. (🙏 Fabien Niel)

Also:

🧑‍💻 Devstral 2 and Mistral Vibe CLI released - Mistral announces Devstral 2, a high‑performing open-source coding model family, and Mistral Vibe CLI, a native terminal agent that can autonomously explore, modify, and orchestrate changes across entire codebases.

🗜️ Poetiq achieves ARC-AGI-2 SOTA at half the cost - Poetiq reports a 54% score on the ARC‑AGI‑2 Semi‑Private Test Set at about $30.57 per problem using a meta‑system that sits on top of Gemini 3, beating the previous best of 45% from Gemini 3 Deep Think at $77.16 per problem. Their key claim is that this new state‑of‑the‑art comes from a learned test‑time reasoning layer that orchestrates an off‑the‑shelf Gemini 3 model, without fine‑tuning the underlying frontier model itself.​ (🙏 Louis Choquel @ Pipelex)

MLOps

⫚ R-Fork accelerates model weight loading - LMSYS introduced R-Fork technology that makes spinning up additional replicas of the same model much faster and cheaper in terms of startup time and I/O, without extra memory copies on the source side. The technique enables more efficient model deployment and scaling. (🙏 Kevin Kuipers)

Programming

👩‍🎨 Cursor introduces visual design mode - Cursor released functionality allowing developers to design directly in their codebase by selecting elements, modifying them visually, and having Cursor write the code. The feature integrates visual design tools with code generation in a single workflow. (🙏 Sacha Morard @ Edgee, Kevin Kuipers, Robert Hommes @ Moyai)

• 🔥 Community take: Still a lot to try, but members are very impressed so far. For Robert, “once it became clear that Playwright was the most used MCP, this made a ton of sense.”

💬 Discussion about AI coding setup - Kasra Aliyon shared an optimized AI coding architecture using approximately 2000 lines of instructions divided across files covering architecture info, best coding practices, and business logic:

• Have a large set of rules, roughly 2,000 lines of instructions split across multiple files.

• The rules cover: a. architecture information b. best coding practices c. business logic.

• We initially included all rules in every request, which caused excessive token consumption and context poisoning. We then moved to directory specific rules, but this proved insufficient. Some rules, such as database constraints, are still required when modifying UI logic, and token usage remained high.

Robert Hommes suggested exploring alternative approaches such as Quibbler to better manage and iterate on large rule sets. In terms of structure, Kasra noted that simple hierarchical organization using headings works well, and that older, more rigid or HTML-like formatting conventions are no longer necessary. (🙏 Kasra Aliyon, Robert Hommes)

Reinforcement Learning

🎓 Stanford Deep RL 2025 course online - Chelsea Finn’s Deep RL course lecture videos from Spring 2025 are now available on YouTube, providing comprehensive reinforcement learning education from Stanford. (🙏 Sophie Monnier)

🧠 Alibaba introduces SAPO reinforcement learning method - The Tongyi Qwen team at Alibaba introduced Soft Adaptive Policy Optimization (SAPO), an innovative reinforcement learning method enhancing RL stability in LLMs by adaptively adjusting update magnitudes, surpassing rigid clipping methods to make large language models more stable and powerful. (🙏 Margaux Wehr)

Robotic, World AI

🔬 Google DeepMind opens robotic AI lab in UK - Google DeepMind announced plans to open a robotic AI lab in the UK focused on discovering new materials, expanding their physical AI research capabilities.

🧠 RL + Robotics dominates NeurIPS 2025 - Analysis from NeurIPS 2025 showed Reinforcement Learning + Robotics has become the largest and fastest-rising field at the world-leading AI conference, driven by massive breakthroughs in embodied AI, autonomous agents, and next-gen robotics platforms, challenging the perception that AI is all about LLMs and GenAI. (🙏 Sophie Monnier)

Other Topics

🎙️ Startup Tribune podcast featuring Joko CTO - Margaux Wehr shared technical podcast episode featuring Alexandre Hollocou, CTO & co-founder of Joko (5m+ users, 30b transactions analyzed), discussing building technical infrastructure at scale. The podcast is co-hosted with AI researcher Louis Abraham from Conception, featuring 45-minute episodes across different sectors monthly.

👉 Article originally posted on WeLoveSota.com

Events

• 🎙️ Voice AI Space - December 10 - Paris - Full day packed with inspiring talks, expert panels, hands-on workshops, and networking opportunities with the Voice AI community at CNIT Paris La Défense.

Audio

• 🎙️ Gradium.ai Announced Seed Round - Kyutai’s first spin-off secured €60 million in seed funding. The company provides state-of-the-art text-to-speech and speech-to-text models via API. (🙏 Laurent Mazare, Pierre Chapuis)

Autonomous Agents

• 📊 tau2-bench as Agent Benchmark Standard - Discussion emerged about tau2-bench becoming the standard way to demonstrate foundational model capabilities for agents. Anthropic used the benchmark to showcase Claude Opus 4.5’s agent performance. The benchmark appears to be increasingly important for validating model effectiveness in agent-based tasks. (🙏 Robert Hommes)

• 🎛️ MCP Functionality Debate - Reddit thread about Model Context Protocol (MCP) functionality was shared, with Garry Tan stating “MCP barely works today.” With people commenting the MCP protocol itself is fine and already useful in real setups, so “barely works” is seen as an exaggeration. The real issues are rough DX, security/auth friction, and inconsistent quality of MCP servers and tooling, which make production use feel fragile today. (🙏 Mario Cornejo)

Biotech Health And Chemistry

• 📊 MLIPAudit Benchmarking Suite - MLIPAudit introduces a physics-based benchmarking suite designed to stress-test the mlip library’s models on downstream tasks such as protein folding and liquid dynamics.

  • 🔥 Community take w/ Sophie Monnier: One key finding is that standard training metrics like RMSE and MAE for energy and force can fail to predict simulation stability, although the library’s SPICE2-trained models generalize remarkably well to biomolecular systems compared with those trained solely on gas-phase data.

• 🏥 Selling AI to pharma reality check - Axiom’s CEO published insights on selling AI products to pharmaceutical companies. The key finding: pharma wants approved drugs, not incremental benchmark improvements. Success requires demonstrating lower toxicity, better efficacy, and evidence progression from cell data to mouse data, ideally reaching human data validation. Beating AlphaFold by 2% on obscure benchmarks carries no weight in pharma sales.

  • 🔥 Community take w/ Felix Raimundo: TL;DR: They want approved drugs and everything else is noise. No one cares that you beat AlphaFold by 2 percent on an obscure benchmark. What matters is lower toxicity, better efficacy, and credible evidence. That means starting with cell data, then moving to mouse data, and ideally human data, though no one can currently deliver that last piece.

• 🧬 Generate:Bio Phase 3 claims - Generate:Biomedicines claimed to be the first company with an AI-designed drug in Phase 3 trials for GB-0895, an anti-TSLP antibody for severe asthma.

  • 🔥 Community take w/ Felix Raimundo: Amusingly, that implies Insilico never actually hit that milestone. But when you look closely:

    • They skipped phase 2 entirely. Maybe you can get away with that for mAbs because the development and safety profiles are so standardized, but it’s still puzzling.

    • The antibody itself is a me-too drug. Tezepelumab hits the same target and was approved in 2021, well before they even began phase 1.

    • It’s their flagship program, which mostly reads as a case study in how to burn a billion dollars.

• 🙏 RFDiffusion3 fully open sourced - The complete RFDiffusion3 codebase and models became available on GitHub through the RosettaCommons foundry repository. This release provides the community with access to advanced protein structure prediction and design capabilities. (🙏 Sophie Monnier)

Image, Video, 3D

• ☀️ Radiance Meshes for Volumetric Reconstruction - Google released major paper from original Gaussian Splatting and NeRF authors introducing radiance meshes. These volumetric triangle meshes use Delaunay triangulation with constant density and linear color per tetrahedron. The trained meshes can be directly integrated into game engines or physics simulations, render at 200+ FPS at 1440p on RTX4090 using hardware rasterization, and support conventional mesh editing tools. The approach delivers super high quality, watertight meshes. (🙏 Samuel McFadden)

• 🎞️ Runway Gen-4.5 Released - Runway launched Gen-4.5 as the world’s top-rated video model, offering unprecedented motion quality, prompt adherence, and visual fidelity. The model represents a new frontier for video generation with state-of-the-art capabilities across all metrics.

• 👓 OpenQuestCapture Released - OpenQuestCapture is an open source Meta Quest 3 spatial capture app for 3D reconstruction and Gaussian splatting by Samuel McFadden. The application captures Quest 3 depth/RGB/pose data with live point cloud visualization and converts to COLMAP format. The hardware is 10x cheaper than professional-grade spatial capture sensors, making spatial capture more accessible. The pipeline can be uploaded to vid2scene.com for cloud processing.

  • 🔥 Community take w/ Samuel McFadden: I’ve been working on this for a while and I’m finally ready to share it. Meta’s Hyperscape Capture is impressive, but you don’t own your data. Quest hardware is surprisingly capable and about ten times cheaper than professional spatial-capture systems, so I wanted to unlock that with an open pipeline.

• 🎥 Kling Launched O1 Model - Kling VIDEO O1 has been announced as a unified multimodal video model that accepts any mix of text, images, elements, or video to generate and edit 3–10s, reference-consistent, highly controllable clips in a single interface. (🙏 Hugo Hernandez, Gabriel Olympie, Pierre Chapuis)

  • 🔥 Community take: Discussion emerged about increasingly confusing model naming conventions across the industry, with multiple companies using similar designation schemes.

• 🎥 SeeDream 4.5 from ByteDance - SeeDream 4.5 has been announced as ByteDance’s upgraded image generation and editing model, improving prompt adherence, multi-image consistency, and high-fidelity visual design for tasks such as reference-preserving edits, posters, and logo layouts.

Infrastructure

• 📈 Data Center Scale and AI Infrastructure Charts - The post argues that recent data contradict some popular tech narratives: AI coding tools’ traffic is rebounding after a perceived collapse, AI exposure does not neatly explain unemployment patterns, and high Series A valuations only weakly predict future startup returns. It also shows that hyperscale AI data centers are rapidly scaling to gigawatt levels, implying massive future energy demand and demonstrating that large physical infrastructure can still be built quickly.

• ⚡️ Ampere AI Pulse Presentation - Sophie Monnier shared a picture from the AI Pulse event. The graph shows that although generative AI will represent less than 40 percent of data-center workloads by 2030, its rapid growth means it will drive most of the power demand, reaching roughly 70 percent of total data-center consumption.

  

Language

• 🔥 Mistral 3 Family Released - Mistral AI announced the next generation with Mistral 3 including three state-of-the-art small dense models (14B, 8B, 3B) and Mistral Large 3, their most capable model to date. Mistral Large 3 uses sparse mixture-of-experts architecture with 41B active and 675B total parameters. All models released under Apache 2.0 license in various compressed formats to empower developers and enable distributed intelligence. (🙏 Kemal Toprak Uçar)

• 🔥 DeepSeek V3.2 “Speciale” Released - DeepSeek dropped V3.2 Speciale, rivaling Gemini 3 Pro in performance. However, the model consumed significantly more tokens, averaging 77,000 tokens to solve Codeforces problems compared to Gemini’s 22,000 tokens. The release represents a major advancement but highlights efficiency trade-offs in reasoning-focused models. (🙏 Hugo Hernandez, Kevin Kuipers)

• 📊 Openrouter’s charts - The report analyzes over 100 trillion tokens of anonymized real-world LLM usage on OpenRouter over roughly the past two years, showing rapid growth of open-source models (especially Chinese OSS), a shift toward medium and large models, and the dominance of roleplay and programming as key use cases, with programming now exceeding half of all token volume. (🙏 Kevin Kuipers, Julien Mangeard)

  • 🔥 Community take: The findings are interesting, but the distribution is inevitably shaped by OpenRouter’s own user base.

Also:

• 🧠 Essential AI Announced Rnj-1 - The release emphasizes the importance of open-source AI development for long-term advancement and equitable diffusion of AI technologies. Founded by Ashish Vaswani, the company focuses on making frontier AI more accessible through open-source models and tools. (🙏 Fabien Niel)

• 🧄 OpenAI’s “Garlic” model codename - Internal leaks revealed OpenAI’s new model carries the codename “Garlic,” continuing their food-themed naming tradition for internal development builds.
  

MLOps

• 🤝 Neptune.ai Acquired by OpenAI - Neptune.ai entered definitive agreement to be acquired by OpenAI, subject to closing conditions. The hosted SaaS service will wind down after a 3-month transition period ending March 4, 2026. Self-hosted customers received direct contact from account managers for smooth transition planning. The acquisition raises questions about alternative MLOps platforms for displaced users.

Programming

• 🧑‍💻 Community take w/ Pierre Chapuis (Finegrain): Switched back from Codex to Claude Code with Opus 4.5 at work and the difference is stark. I don’t see how anyone would choose non-Anthropic models when they have the option, with the caveat that I haven’t tried Gemini 3 for this yet. Compared with Codex, the speed stands out first, but it also produces better code, understands intent more reliably, and responds more effectively to guidance. The one weakness is handling .pbxproj files for iOS work; it struggles there, so it’s safer to update those manually, though it won’t touch them unless you explicitly ask.

Robotic World Ai

• 🤖 UMA Bot Went Public - UMA (Universal Mechanical Assistant) officially launched their public website. The company develops AI and robotics to shape a new economic and societal era, designing general-purpose mobile and humanoid robots with human-level dexterity and deep understanding of the physical world. The team is accelerating development and growing multidisciplinary capabilities. (🙏 Pierre Chapuis)

Other Topics

• 😓 US Gen Z Sentiment on GenAI - Airbuds user data revealed 70% of users (predominantly 15-20 year olds from US) are “very against” or “against” GenAI, with only 30% neutral or favorable. Key concerns include job and housing threats, AI slop fatigue from GenAI flooding feeds, uncanny valley effects in visuals, and perception of GenAI music as DSP scamming or artist labor replacement. The indie culture emphasizes authenticity, potentially biasing the sample compared to general public. (🙏 Gawen Arab @ Airbuds, Niko Hosta)

• 🧠 Neuralink Overview Fall 2025 - Neuralink released overview presentation covering company history, Telepathy product and future roadmap, and engineering challenges. (🙏 Fabien Niel)

• 😈 MCP Security Joke - Guillaume Laforge from Google trolled at Tech Rocks Summit with image stating “The S in MCP means security” highlighting ongoing discussions about Model Context Protocol security considerations. (🙏 Guillaume Lesur)

Ask For Help

• 🇫🇷 Voice Accent Conversion Request - Vianney Lecroart is seeking for tools to convert video audio with French-accented English to native English accent while maintaining lip sync. Krisp AI was mentioned as a real-time solution, though it lacks features for pre-recorded video processing. (reach out to Vianney)

• 🤨 DoIT to Ingram Micro Transition - Maxence Maireaux received email about Root Account changes switching from DoIT to Ingram Micro without clear explanation, seeking information from others about the transition. (reach out to Maxence)

• 🙋‍♂️ AI Adoption Framework Request - Request for frameworks covering AI adoption in medium-sized Product & Engineering organizations, ideally addressing onboarding, adoption, ROI, security, and engineering KPIs like code quality and review coverage. Mentioned search for AI version of DORA metrics. (reach out to Lior Oren)

New Members

• 🇫🇮 Kasra Aliyon (Kopilo) - Co-founder at Kopilo, an AI-native workspace for scientific researchers described as “Cursor for Research.” AI researcher for 6 years building his third startup in the AI/ML space, currently hands-on developing AI agents. Hosts podcast “The AI Era” exploring the intersection of Humanity and AI. 📍Based in Helsinki, Finland.

• 🇫🇷 Maziyar Panahi (OpenMed) - Data and AI infrastructure lead at CNRS. Built platforms holding 360B+ web records and operates a 120+ node Hadoop cluster for large-scale ML. Contributes to open-source medical AI and post-training/RL. Former heavy-metal guitarist. 📍Based in Paris, France.

• 🇫🇷 David Martins Gonçalves (Notify AI) - CTO and co-founder of Notify AI, with 20+ years as an entrepreneur focused on scalable AI decisioning for CRM. Founded companies across Europe and South America. Passionate about solving real business problems. Enjoys boxing and reading. 📍Based in Paris, France.

• 🇫🇷 Sébastien Blanc (Java Champion) - Java Champion and Staff Developer Advocate blending Java, platform engineering, and AI governance. Known for helping teams modernize legacy systems. Frequent conference speaker, padel player, Half-Life fan, and owner of 5 cats. 📍Based in Vallauris, France