We now support Agent Skills - the open standard created by @AnthropicAI for extending AI agents with specialized capabilities. Create skills once, use them everywhere. 🔗 https://t.co/4GomgRJ21O https://t.co/MHA4SBzVNN

Tomorrow morning (8AM Pacific on Dec. 19th) join @digitarald, @timrogers, and me as we take a look at #AgentSkills in @code and #GitHubCopilot Cloud Agent and more! https://t.co/4DhMVQx7X0 #vscode

Yann LeCun says reaching human-level AI won't be a sudden event, but a gradual evolution "optimistically, we might reach human-level, or at least dog-level, intelligence within 5 to 10 years" However, if we run into unexpected obstacles, it may take 20 years or more

Yann LeCun (@ylecun ) beautifully explains how the architecture and principles used to train LLMs can not be extended to teach AI the real-world intelligence. In 1 line: LLMs excel where intelligence equals sequence prediction over symbols. Real-world intelligence requires learned world models, abstraction, causality, and action planning under uncertainty, which current next-token training does not provide. He says current LLMs learn by predicting the next token. That objective works very well when the task itself can be reduced to manipulating discrete symbols and sequences. Math, physics problem solving on paper, and coding fit this pattern because success largely comes from searching and composing the right sequences of symbols, equations, or program tokens. With enough data and scale, these models get very good at that kind of structured sequence prediction. Real-world intelligence is different. The physical world is continuous, noisy, uncertain, and high dimensional. To act in it, a system needs internal models that capture objects, dynamics, causality, constraints from the body, and the outcomes of actions over time. Humans and animals build abstract representations from rich sensory streams, then make predictions in that abstract space, not at the raw pixel level. That is why a child can learn intuitive physics, plan multi-step actions, and adapt quickly in new situations with little data. His claim about saturation follows from this gap. Scaling token prediction keeps improving symbol manipulation tasks like math and code, but it hits limits on embodied reasoning and common sense because text alone does not provide the right learning signals for world models. Predicting the next word cannot efficiently teach contact forces, affordances, occlusion, friction, or how actions change the state of the environment. For that, he argues we need architectures that learn abstractions from sensory data and predict futures in abstract latent spaces, then use those predictions to plan actions toward goals with built-in guardrails. --- From 'Pioneer Works' YT Channel (link in comment)

“Elon Musk and Yann LeCun playing marbles” made by @grok Yann doesn’t really look like Yann https://t.co/AuAuN285OA

“Elon Musk and Yann LeCun playing marbles” made by @grok Yann doesn’t really look like Yann https://t.co/AuAuN285OA

Introducing DexWM: Dexterous Manipulation World Model tl;dr: train on human videos; fine-grained actions; hand-consistency loss; DexWM+MPC -> zero-shot dexterous manipulation w/ @_amirbar, @DavidJFan, @JimmyTYYang1, @GaoyueZhou, P. Krishnamurthy, M. Rabbat, F. Khorrami, @ylecun https://t.co/cn2D0mvJyg

Meta just released MapAnything on Hugging Face A universal transformer model for metric 3D reconstruction It supports 12+ tasks like multi-view stereo and SfM in a single feed-forward pass https://t.co/aUtZ1rymcF

We were thrilled to join forces with @cusp_ai, @SakanaAILabs, @SamsungNext, & @nvidia during @NeurIPSConf to bring to life the panel event: ‘AI for Science: Algorithms to Atoms.’ ⚛️ Our esteemed panelists and moderator (@BillDally, @wellingmax, @AnimaAnandkumar, Marc Tessier-Lavigne, @hardmaru , Trenton Jerde) discussed what AI has already made possible across scientific domains, where the next breakthroughs may emerge, and how far automation of the scientific method can go. We’re delighted to now share the replay of this thoughtful, insightful, and important discussion and hope you enjoy it. Please reach out to continue the conversation… 📺: https://t.co/qm9PAzzTCf

Applied Teamに関する詳細については、こちらの紹介をご覧ください。 https://t.co/11hP67FI84 https://t.co/PxwqbnGjak

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5 AI Evals Traps Every AI Team Should Know About: (and what actually works) https://t.co/iIfUFSMmIr

5 AI Evals Traps Every AI Team Should Know About: (and what actually works) https://t.co/iIfUFSMmIr

Thinking Machines chief scientist John Schulman on what’s changed in AI since 2015–2017: “Previously the people were a bit weirder.” “Engineering skill matters more now… as opposed to research, taste and the ability to do exploratory research.” “There’s so much low hanging fruit just from scaling the simple ideas and executing on them well.” “People who have more of a software engineering background have more of an advantage now.” @johnschulman2 @thinkymachines @mntruell @cursor_ai

Atlas weekly release is here, last one before the holidays: - Multi-profile: Multiple browser profiles ('personal', 'school', 'work') for the same ChatGPT login; multiple ChatGPT logins coming soon - Selectively import things like extensions or passwords, even after onboarding - Hover to see vertical tabs when they are closed - More DevTools fixes (no devices tab yet!) - Lots of bug fixes and polish (especially for empty responses, tabs, or high memory use) We're working on tab groups, and they're feeling great, but will be out shortly after the holiday. Just hit "update" in the top right. https://t.co/MlSRZjHPWB

NEURALINK’S TECH IS GIVING VOICES BACK TO THE VOICELESS Science made personal. Real tech, real voice, real impact. Voice Wave: * Brad, diagnosed with ALS, lost his ability to speak * He became the third person to receive a Neuralink brain implant * The implant helped him reconnect – voice, emotion, presence * From silence to communication, powered by thought This is what it looks like when Neuralink science gives humanity the mic back! Source: @Neuralink

The AI discourse continues to confuse, but the real breakthroughs are clear: agents negotiating across companies, simulation-trained systems, ambient intelligence that knows when to act, spatial intelligence understanding physical reality, and AI that's consistently excellent at complex business tasks. My take on how #EnterpriseAI will transform in 2026 here: https://t.co/YRrq8O8QmY #BigIdeas2026 #FutureofAI #AIResearch

Transformers v5 going all-in on PyTorch, new ecosystem projects, and major moments from NeurIPS 2025 headline the December PyTorch newsletter. Catch up on the latest from the PyTorch community, including ecosystem updates, PyTorch Conference 2025 recaps, and recent member and community blogs. 🔗 Read the full newsletter: https://t.co/pILknhrXVT 📨 Subscribe to receive the PyTorch newsletter directly in your inbox: https://t.co/3E2i9TboaZ #PyTorch #AIInfrastructure #OpenSourceAI

This is a room with >2000 CNC mills near Shenzhen that I've been inside. The mills are arranged in cells with multiple tended by a robot on tracks, so there are very few people working on the floor. There are dozens like this in China. What's the biggest similar facility in the US?

I've been chatting with @adam__conway for the last 2.5 months about agents and rollbacks. On my last team, we got it wrong. On several of my friend's teams, they admit they're still getting it wrong. MCP further muddies the water. Read Adam's proposal: https://t.co/auFZskTGhf

ELON MUSK: WE SHOULD HAVE A SECOND PLANET TO PRESERVE CIVILIZATION "In my view, we should have a second planet to preserve civilization. Because let's say hypothetically I mean, maybe those are the ruins of a long-dead civilization That will probably happen to Earth at some point. You know, it's a matter of time before we get hit by an asteroid, or maybe we annihilate ourselves with nuclear war, or supervolcanoes"

As part of our partnership with @ENERGY on the Genesis Mission, we're providing Claude to the DOE ecosystem, along with a dedicated engineering team. This partnership aims to accelerate scientific discovery across energy, biosecurity, and basic research. https://t.co/cCywLCjK2w

Monitoring a model’s chain-of-thought is far more effective than watching only its actions or final answers. The more a model “thinks” (longer CoTs), the easier it is to spot issues. https://t.co/e1AgGXSRvZ

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New paper: We train Activation Oracles: LLMs that decode their own neural activations and answer questions about them in natural language. We find surprising generalization. For instance, our AOs uncover misaligned goals in fine-tuned models, without training to do so. https://t.co/ePK2gG5Rik

@TaylorLorenz wtf is a radicalized soccer mom? https://t.co/STDfYIpLwT

New paper, open access, feedback very welcome. Any complaints will be handled in the fullness of time, by the appropriate authorities, once you have located the correct form etc https://t.co/PZqBxc9QK3 https://t.co/5XthCYMvuh

‘ChatGPT detector’ catches AI-generated papers with unprecedented accuracy https://t.co/WoaQH8uIjF

Ok this is kinda neat: If you give https://t.co/XTEx6kY7EN a scientific paper it will generate a network of references and citations! https://t.co/E93tAG5vMc

Clear evidence that employers discriminate against nonbinary individuals. All-else-equal, disclosing that one uses "they/them” pronouns substantially lowers the chances of getting a job interview. https://t.co/VJ8LlQR77H https://t.co/raLGvf2h4v

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Claude Code can now browse the web! You can build some insane things with this. I just built a little subagent that tracks & reports AI-related posts on X. Broken X algo? No worries! Just build a personal agent and let it help you filter out and track what you want. https://t.co/XGOtdF8WiT

A new 25-year study found that higher intake of high-fat cheese and cream was associated with a lower risk of all-cause dementia. Moo. https://t.co/Eoa256jsNB

“Re-inventing the wheel” should mean exactly the opposite of what it means, given that there is a decent chance that the wheel for transportation was invented just once, in the Carpathian Mountains around 3900 BC & was never independently re-invented by other societies afterwards https://t.co/lXYBSnlqfP

Is XRP crashing? The sustained break below $2 signals trouble https://t.co/n94cPbGD5a @godbole17 @coindesk