The original "AI Winter" was primarily a government funding phenomenon [1]. There was no "bubble" in the private sector. I.e., the winter was the result of resp

The original "AI Winter" was primarily a government funding phenomenon [1]. There was no "bubble" in the private sector. I.e., the winter was the result of responsible people in government realizing the hype was over-extended and standing up for the taxpayer. Progress would be made, eventually, but not in that moment. (Those people were correct, btw.) > But beneath the surface, there are rampant issues: citation rings, reproducibility crises, and even outright cheating. Just look at the Stanford students who claimed to fine-tune LLaMA3 to have be multimodal with vision at the level of GPT-4v, only to be exposed for faking their results. This incident is just the tip of the iceberg, with arXiv increasingly resembling BuzzFeed more than a serious academic repository. Completely agreed. Academia is terminally broken. The citation rings don't bother me. Bibliometrics are the OG karma -- basically, fake internet points. Who cares? The much bigger problem is that those totally corrupt circular influence rings extend into program director positions and grant review committees at federal funding agencies. Most of those people are themselves academics (on leave, visiting, etc.) who depend on money from the exact sources they are reviewing for. So this time is their friends turn, and next time is their turn. And don't dare tell me that this isn't how it works. I've been in too many of those rooms. It's gotten incredibly bad in in ML in particular. Our government needs to cut these people off. I am sick of my tax money going to these assholes (via the NSF, DARPA, etc.). Just stop funding the entire subfield for a few years, tbh. It's that bad. On the private sector side, I think that the speculative AI bubble will deflate, but also that some real value is being created and many large institutions are actually behaving quite reasonably compared to previous nonsense cycles. You just have to realize we're mid-late cycle and companies/groups that aren't finding PMF with llm tech in the next 2-3 years are probably not great bets. -- [1] https://en.wikipedia.org/wiki/Lighthill_report https://en.wikipedia.org/wiki/Lighthill_report