It sounds insane, because we're used to a particular way of doing research: of giving and receiving credit, of counting beans, of hiring, recruiting, and promoting. And the machine god came to crush that game. The old game is dead. That reasonably causes incredible amounts of dread for many folks, who understand this as the death of research. But it's not about Research, but the way we played the game. The old game was built around scarcity, scarce compute, scarce students, scarce hours, scarce people who knew the right technique and method etc. Most of a research career went into managing and playing along these constraints. Those walls just came crushing down. One person with a good question can now do what used to take a lab and five years. You do not need permission, you do not need a big grant, you do not need a professor or researcher title, or a team of twenty experts , or one thousand gpus to stare straight into the first light of the universe. How absolutely incredible

Our 4th world modeling workshop will be looking at *Physics*! Happening at the Aspen Center for Physics end of February (wmw-aspen.github.io) If you are interested in presenting, submit your abstract here: docs.google.com/forms/d/e/1F… Deadline on October 9th, 1 page Abstract!

I’m a professor in the US, where I lead an AI research group. This is my series on PhD. Tip: Learn to explain your research without slides. If you can get another scientist/researcher interested in your problem during a 2-minute coffee conversation, conferences become much more useful.

Defended my PhD yesterday! I wrote a blogpost that distilled my research into a single takeaway (in 🧵) Thank you @rdnowak for the amazing four years. Now that I see it, he truly has the magic potion that helped so many of his students turn into great researchers.

It’s official: I got my tenure! Immensely grateful to my colleagues, students, friends, and family who have supported me on this journey. On, Wisconsin!

It was amazing to be part of this effort. Huge shout out to the team, and all the incredible pre-training and post-training efforts that ensure Gemini is the leading frontier model! deepmind.google/discover/blo…

Working in active learning, I often hear a common complaint — active learning doesn’t work sometimes. Our ICML 2025 paper JUST WORKS* when you have class imbalance. @rdnowak will present it Tuesday afternoon. Short 🧵below Paper: arxiv.org/abs/2312.09196

Releasing HumorBench today. Grok 4 is🥇 on this uncontaminated, non-STEM humor reasoning benchmark. 🫡🫡@xai Here are couple things I find surprising👇 1. this benchmark yields an almost perfect rank correlation with ARC-AGI. Yet the task of reasoning about New Yorker style cartoons/captions can’t be more different from tasks in ARC. 2. LLMs trained purely on STEM data does improve capability in non-STEM humor reasoning. Project page: reubennarad.github.io/Humor-… Paper: reubennarad.github.io/Humor-…

Whoa... Grok 4 beats o3 on our never-released benchmark: HumorBench, a non-STEM reasoning benchmark that measures humor comprehension. The task is simple: given a New Yorker Caption Contest cartoon and caption, explain the joke.