ICML’s Statement about subversive hidden LLM prompts We live in a weird timeline…

Not Even Bronze: Evaluating LLMs on 2025 International Math Olympiad 🥉 Nice blog post from the team behind MathArena: Evaluating LLMs on Uncontaminated Math Competitions () providing independent analysis of LLM performance on IMO.

Not Even Bronze: Evaluating LLMs on 2025 International Math Olympiad 🥉 Nice blog post from the team behind MathArena: Evaluating LLMs on Uncontaminated Math Competitions () providing independent analysis of LLM performance on IMO.

Engineers spend 70% of their time understanding code, not writing it. That’s why we built Asimov at @reflection_ai. The best-in-class code research agent, built for teams and organizations.

Humanity has prevailed (for now!) I'm completely exhausted. I figured, I had 10h of sleep in the last 3 days and I'm barely alive. I'll post more about the contest when I get some rest. (To be clear, those are provisional results, but my lead should be big enough)

Some updates 🚨 I finished my Ph.D at @uwcse in June 2025! After a year at AI2 as a Research Scientist, I am joining CMU @LTIatCMU & @mldcmu (courtesy) as an Assistant Professor in Fall 2026. The journey, acknowledgments & recruiting in 🧵

Hikaru Utada and Yuval Noah Harari talk about The Evolution of AI and Creativity Gotta admit, this was not on my bingo card!

Excited to take part in @TEDAISF this fall!

1 decade ago: Reinforcement Learning Prompt Engineer in Sec. 5.3 of «Learning to Think …» [2]. Adaptive Chain of Thought! An RL net learns to query another net for abstract reasoning & decision making. Going beyond the 1990 World Model for millisecond-by-millisecond planning [1].  [2] J. Schmidhuber (JS, 2015). «On Learning to Think: Algorithmic Information Theory for Novel Combinations of RL Controllers and Recurrent Neural World Models.» ArXiv 1210.0118  [1] JS (1990). “Making the world differentiable: On using fully recurrent self-supervised neural networks for dynamic reinforcement learning and planning in non-stationary environments.» TR FKI-126-90, TUM. (This report also introduced artificial curiosity and intrinsic motivation through generative adversarial networks.)

If you are thinking about world models or neural sims and don't know where to start, check out the OG paper on world models from @hardmaru and @SchmidhuberAI - It is super clear to read and get the basics - you can reproduce it on your Mac or any local machine - you can steadily upgrade it be even more powerful If Karpathy would teach world models this is the paper he would do deep dive into.