I've been asked by few first year PhD about how to start LLM research on X, say long context modeling. My number one suggestion -- though it seems a bit of unconventional -- is *not* to read any papers related to long-context, but to talk to the model - Talk to the model about a text book, course slides, financial reports, novels, nonfictions, any... See more

@emollick Put in the reps. If you aren't hitting the chatGPT cap multiple times a day, you have 0 business reading a research paper The open area of research is what can we use LLMs for, not how do we build better LLMs and the papers are outdated anyways

It is odd when folks get mad when I say AI is already useful. We are only 18 months into LLMs & there have already been many controlled trials finding LLMs are useful, firms have public case studies with real metrics, etc Lots of reasons to critique AI, “uselessness” isn’t one.

A few places you should probably use AI to help you, based on the research we have (but do whatever you want): -Idea generation -Writing (not writing for you, maybe, but second opinions/proofing/etc) -Advice/finding frameworks to solve problems -Summarizing documents & meetings

Learned something interesting from the CEO of a fairly big tech co. Usually 28 year olds are more productive programmers than 22 year olds, because they have more experience. But apparently 22 year olds are now as good as 28 year olds because they're more at ease using AI.

AI will magnify the already great difference in knowledge between the people who are eager to learn and those who aren't.

In a situation like this, there are two general pieces of advice one can give: keep your options open, and pay close attention to what's happening. Then if you can't predict the changes AI will cause, you'll at least be able to react quickly to them.