This is hacking. Don't confuse it with AI.

X/Twitter user numbers now down by almost a third over the last year in the UK, and by almost a fifth in the US.

Time to enjoy yet another way GenAI is more of a headache than enterprises realized: Data deletion takes on a whole new meaning when it’s possible to recover data a company didn’t know it had. I explain in the blog 👇 bit.ly/quaesita_linkedinopti…

It's a bit sad and confusing that LLMs ("Large Language Models") have little to do with language; It's just historical. They are highly general purpose technology for statistical modeling of token streams. A better name would be Autoregressive Transformers or something. They don't care if the tokens happen to represent little text chunks. It could just as well be little image patches, audio chunks, action choices, molecules, or whatever. If you can reduce your problem to that of modeling token streams (for any arbitrary vocabulary of some set of discrete tokens), you can "throw an LLM at it". Actually, as the LLM stack becomes more and more mature, we may see a convergence of a large number of problems into this modeling paradigm. That is, the problem is fixed at that of "next token prediction" with an LLM, it's just the usage/meaning of the tokens that changes per domain. If that is the case, it's also possible that deep learning frameworks (e.g. PyTorch and friends) are way too general for what most problems want to look like over time. What's up with thousands of ops and layers that you can reconfigure arbitrarily if 80% of problems just want to use an LLM? I don't think this is true but I think it's half true.

🎉Congrats to @OpenAI for releasing o1: - Economics: @tylercowen asked o1 basically to write a college essay - Genetics: @catbrownstein asked o1 to help her reason through "n of 1" cases - medical cases that nobody has ever seen - Physics: @mariokrenn6240 used o1 to draft and reason through complex quantum physics equations - Code: @ren_hongyu prompted a full snake game and it was generated zero shot, working perfectly, and obeyed instructions to add obstacles

the european mind cannot comprehend lil jon doing georgia's roll call

5. There Is A Lake In Finland, That Looks Like Finland

It’s like fractals. The 1% is insanely better at math than the 99%. The 0.1% is yet again insanely better. And yet again the 0.01%. The 0.0001% is a whole different species. I have friends in the 0.00001% and they scare the hell out of me. And then there’s Terry Tao.

I am at #ICML2024 presenting our work on the information complexity of stochastic convex optimization with my amazing collaborators. Oral talk: Thu 25 Jul 11:15 a.m. Poster: Thu 25 Jul 11:30 a.m. Arxiv Link: arxiv.org/abs/2402.09327 ICML link: icml.cc/virtual/2024/poster/…