Associate Professor CS/stats UC Berkeley. Former Research Scientist at Google DeepMind. ML/AI Researcher working on LLMs and deep learning. PhD at Stanford.
O1-pro is pretty useless for research work. It runs for near 10 min per prompt and either 1) freezes, 2) didn't follow the instructions and returned some bs, or 3) just made some simple error in the middle that's hard to find. @OpenAI@sama@markchen90 refund me my $200
What most people don't realize is that IMO (and IOI, though to a different extent) aren't particularly hard. They're aimed at high schoolers, so anyone with decent uni education should be able to solve most of them.
Returning to the bay area after 9 years! Moving to UC Berkeley in statistics and eecs! It's been a great 6 years at Princeton, but I am so happy to be back! Finally there will be edible sushi!
Our latest post explores on-policy distillation, a training approach that unites the error-correcting relevance of RL with the reward density of SFT. When training it for math reasoning and as an internal chat assistant, we find that on-policy distillation can outperform other
See below on what Zuckerberg is looking for in star recruits worth $100m pay packages for Meta’s plans in Artificial Intelligence.
But weren’t some people saying calculus is no longer useful in the AI age? 🤔