We've lost an absolute giant today. RIP Dimitri Bertsekas. His probability and optimization books got me through my masters. Massive loss for the MIT community and the field.
interested in 3D vision, motion, driving, or robotics? consider applying to our graduate programs. the fall deadline is May, 15.
we do our best to provide a research environment where students can reach their potential and publish in top-tier AI venues.
we regularly collaborate with leading AI labs worldwide and offer EU-level scholarships (+dorm/housing support), solid GPU resources (a decent local cluster + access to supercomputers like Leonardo and MareNostrum), and a fun, supportive lab environment :)
https://t.co/E2HxcBAcxq
I work on the JAX team. If you're new to the field ignore this bait. The things you should focus on are understanding the math and how to program accelerators - really master your hardware and your methods. We try to make a great tool but don't obsess over tools early.
Swiss AI Visiting PhD Program at EPFL. Deadline Feb 28.
"The program provides a fellowship contribution of CHF 2,500 ($3200) per month, access to the Alps supercomputer, and eligibility for a post-visit continuation grant of up to 50k GPU hours. The call is open to PhD students enrolled outside Switzerland, with applications supported by EPFL PIs contributing to the Swiss AI Initiative. The application closes on February 28."
https://t.co/ZlB7Mm1SFj
@ICepfl@EPFL_AI_Center
We are hiring full-time ML researchers and PhD-level interns at Apple! We have exciting projects in AI for Science, science of LLMs as well as diffusion models. Feel free to directly reach out via DM or e-mail me personally.
A whole lot of BS political views basically amount to assuming that life in our hard won civilisations is just the way things are, and that you can simply remove the foundations.
Only a society protected by vaccines produces anti-vaxxers. Only a society with a strong military produces pacifists. Only a society with large scale industrial farming produces organic foodies. Only societies with cheap energy produce degrowthers.
You don’t get to enjoy the ends whilst condemning the means, and still be taken seriously.
You've got a couple of GPUs and a desire to build a self-driving car from scratch. How can you turn those GPUs and self-play training into an incredible looking agent? Come to W-821 at 4:30 in B2-B3 to learn from @Mdjxjxnsk@tw_killian@ozansener
We are presenting two papers at #ICML2025
Robust Autonomy Emerges from Self-Play https://t.co/KNtuLpbq8N
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration https://t.co/8rg9ZOdaJq
Gezi'de nasıl omuz omuza direndiysek, bugün de öyle direniyoruz.
Ekrem Başkan bugün misafirliğimize geldi, ona çok iyi bakacağız hiç merak etmeyin.
Beraber çıkacağız, beraber mücadele edeceğiz; kurtuluş yok tek başına, ya hep beraber, ya hiçbirimiz!
Hiring researchers and engineers for a stealth, applied research company with a focus on RL x foundation models. Folks on the team already are leading RL / learning researchers. If you think you'd be good at the research needed to get things working in practice, email me
The most incredibly prescient words by my dear friend Prof. John Etchemendy, former Provost of @Stanford , codirector of @StanfordHAI , and one of the most thoughtful leaders of America’s higher education! https://t.co/tlrIL1Jp4N
We've built a simulated driving agent that we trained on 1.6 billion km of driving with no human data.
It is SOTA on every planning benchmark we tried.
In self-play, it goes 20 years between collisions.
Incredibly exciting work! https://t.co/aJEGtpF9eL. Cooperative, safe, driving can arise at scale from self-play training without human data, just as my group saw in Overcooked a few years ago. Caveat: in simulation. Bravo @EugeneVinitsky and coauthors!
Excited to share our new pre-print https://t.co/FtT3hkHKeG
We train a digital agent that solves diverse day-to-day tasks from the AppWorld benchmark by interacting with its stateful environment using API calls. AppWorld is hard! The previous best open-weight agent (Llama 3 70B) reached only a 7% success rate on the hardest test split. Our RL algorithm, LOOP - a PPO variant with Monte Carlo baselines - achieves a 45.7% success rate, 24% over the base Qwen 2.5 32B, and 9% higher than a much larger OpenAI o1.
🚀 We are hiring full-time ML researchers and PhD-level interns!
Join us for exciting projects in AI for Science (weather and climate models) and understanding LLMs.
Full-time role: https://t.co/R3Y8p3CgyL lists US but EU is also OK—apply regardless of location preference!