Dan Roy

@roydanroy.bsky.social

Research Director, Founding Faculty, Canada CIFAR AI Chair @VectorInst. Full Prof @UofT - Statistics and Computer Sci. (x-appt) danroy.org I study assumption-free prediction and decision making under uncertainty, with inference emerging from optimality.

Someone has suggested I check out bsky again. So I'm back looking around here. Notification list is kinda boring. So any good conversations going on? Perhaps about LLM/AI reasoning?

I got to ski Revelstoke this winter break. Couple observations: the price of receiving 600 cm of snow by Jan 8 is that it is constantly snowing. Saw almost no sun the whole time and the peak was often in whiteout conditions (though North Bowl was always clear…). See image for more.

Bild

Multiple friends have likely lost their homes in Los Angeles. Can’t imagine how disorienting this would be. They had only minutes to flee and grab belongings.

OK. Practical question times. How are you adjusting your research given progress in reasoning style models? Also how are you adjusting the way you work?

Now that I've had a taste of X without post length limitations, I've got to say that it is quite annoying have to fit tweets into 256 characters here on bsky. On X, when they get to long, they go below the fold, and so you're still incentivized to make it short. Can't we have that here?

Has anyone out there compared the GPU/memory specs for the new Macbook Pro M4 Pro/Max computers to the requirements to run inference in the more interesting open source LLM models, especially those aimed at reasoning? [1/2]

NeurIPS Test of Time Awards: Generative Adversarial Nets Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, Yoshua Bengio Sequence to Sequence Learning with Neural Networks Ilya Sutskever, Oriol Vinyals, Quoc V. Le

Waterloo is facing a 75 million CAD deficit and so they are implementing a hiring freeze. As one of the world’s top universities, it is ridiculous that Ontario is not funding it fully. It has generated so much SV wealth, I suggest a SV billionaire solve this deficit and then some.

Hot take: Working another weekend this semester, I am left wondering: Why does the #NLProc publication process have so much artificial urgency baked into it? Requiring responses within 24h, emergency reviewers, everything urgent. Like, why? Slow science can also be a community goal.

Has anyone asked whether scaling laws are surprising or not? (Not only to meat puppets, but surprising in the real sense of "it could have been different".) Universal learning rates look like scaling laws in the non-extreme case, where the class isn't trivial or impossible. No compute there though.

Hey... anyone know w.t.f. runs BlueSky? Does this sit on top of mastodon? Can we edit the software? How do we tweak our feeds? E.g., if I'm in the mood for ML or for politics or whatever?

Reviewing is dead. I just read some ICLR reviews. Absolutely junk. No insight. Written by humans, but could have been written by a chatbot or teenager who had read a few dozen reviews. Why do we think this is useful? Only 5% (if that!) of the community has worthwhile opinions.