I am looking to hire PhD students, post-docs, and ML researchers in our Paris office interested in collaborating on fundamental research in AI model safety, not safety rules, not AI policy, not post hoc guardrails, not RLHF. We also have offices in Singapore, NYC, and Montreal. @amilabs #aisafety

The recording of my ICML 2026 keynote is online. I explain why real world problems can only be solved by world models not generative models in real-time. icml.cc/virtual/2026/invited…

We can argue forever whether the term should be LLM “hallucination” or “confabulation” but language is a democratic thing. The global AI scientific community has adopted the term “hallucination” because it is easy to understand and remember and easier to pronounce. Only the anglophone elite promots the term “confabulation” and it doesn’t work because nobody else uses the word in daily contexts.

Jensen Huang promotes open-source LLMs for innovation. Great. The next step is democratizing compute. High GPU costs remain one of the biggest barriers to academic research and grassroots innovation. Imagine the impact if NVIDIA also expanded free or heavily subsidized compute for researchers and open-source projects. Open models need accessible compute to truly unlock innovation.

Speaking from my American experience only here. Some people complain about large industry funded research. Don’t forget that almost all of paradigm changing research that led to modern AI came from either large industry labs - Bell Lab, IBM Labs, Xerox Parc, Microsoft, Google, GDM, FAIR, etc etc. or from the millitary defense funding. For modern AI, ideas that come from universities simply are not scabale to real impact in our area without industry research taking over. This was true before the era of LLMs. Many people in academic without industry experience also do not know what it takes to scale AI research to real production impact. So my (radical) view is that universities should work with industry if we want to have real impact OR focus on more theorectical and field research that does not require resources from either the private sector or the defense budget. More theoretical research does not need such funding. Linguistics certainly doesn’t. So doing research in language and language per se, not LLMs, not chatbots and not agents, does not need to be in any industry lab.

Giving my keynote at #icml in one hour icml.cc/virtual/2026/invited…

Thrilled to announce the Wearable AI Workshop at ECCV 2026 🎉 that we're organizing with an awesome group of folks across Meta Reality Labs, AMI Labs, HKUST, Georgia Tech, UCF, and U. of Edinburgh. If you work on egocentric perception, multimodal assistants, or long-form video understanding, definitely consider participating. Details below 👇 🔬 Wearable AI Workshop @ ECCV 2026 | Malmö, Sweden Join us to advance the science of real-time, multimodal, context-aware assistants — with access to the largest egocentric wearables dataset ever released, $21K in challenge prizes, and a venue to shape the research agenda alongside leading groups in the field. 🏆 Grand Challenge — $21K in Prizes Compete on the largest egocentric wearables dataset ever released (5,000+ hours) across three tracks: Proactive AI — Predict when and how to proactively engage users Multi-Turn Conversations — Streaming answer prediction from egocentric video Long Video Q&A — Temporal grounding and recall over 30+ minute videos 🎤 Confirmed Keynote Speakers Kristen Grauman (UT Austin) — Professor, Computer Vision Group Dima Damen (U of Bristol, Google DeepMind) — Professor of Computer Vision Raffay Hamid (Meta Reality Labs) — Distinguished Engineer, GenAI If you work on egocentric vision, long-form video understanding, conversational AI, or on-device inference — this is your venue. 📅 September 2026 · 📍 Malmö, Sweden 🔗 Workshop URL: wearable-ai-workshop.github.… #Meta #MetaRealityLabs #MetaAI #AMIlabs #HKUST #UTAustin #GeorgiaTech #UniversityOfEdinburgh #UniversityOfBristol #ECCV #ECCV2026 #WearableAI #EgocentricVision #ComputerVision #MultimodalAI #AIResearch

Machines do not have intents. Humans do. Machines do not have feelings. Humans do. Machines do not have psychology. Humans do. Machines can misbehave, but only humans can be evil. Stop virtual signaling and ethics washing and focus on real work on responsible AI, which starts with being responsible humans. #anthropic

Anthropic is trying to anthropomorphize model behavior and fearmonger—but at the same time, profit from it. I admired them at the beginning, but now I am convinced that they are either too stupid to confuse model behavior with human-like intent, or just evil in trying to profit from it. Neither is a good sign of where this company is going.

So excited to have Julia Kempe with us in Paris! @lab_kemp

Met the goat @ylecun Ty @amilabs for the lovely event~ so many lovely amazing people <3

I will be in Rio. I am looking to talk to former and current colleagues and students interested in working on vison language word models and human-agent interactions in the physical world.

Be still my trekkie heart…

I am hiring researchers and builders for our #Paris team to build advanced machine intelligence that is fundamentally human-centered. amilabs.xyz

Meta’s former chief AI scientist has long argued that human-level AI will come from mastering the physical world, not language. His new startup, AMI, plans to prove it. wired.com/story/yann-lecun-r…

AI pioneer Yann LeCun's new startup has raised $1 billion in initial funding bloomberg.com/news/articles/…

I am happy to share that I have joined forces with @ylecun and fellow founders as Co-Founder and Chief Research & Innovation Officer at AMI - Advanced Machine Intelligence. I will lead research initiatives that push AI to be genuinely human-centered - AI that perceives, learns, reasons and acts like we do and in our best interest. I am thankful for the trust placed in us and deeply aware of the responsibility we share to making the world a better place through our work everyday. Join us!