Tenured professors do often fail large swathes of the class, and it's not hard to stand their ground because academic freedom is still very important in universities. This is not generally true for non-tenured and adjunct professors, but for a different reason -- their job review rely on a large part on student feedback forms, and failing students are not happy students.
The idea that if only all professors stood their ground then somehow students will be motivated to study doesn't pan out in practice, though. There is already a significant number of students who are perpetually struggling. They are missing basic prerequisites, and instead of catching up on them, they repeated try and fail at learning the same materials, passing only when they got a lenient instructor. The problem compounds because failing brings helplessness and exacerbates their mental issues, which brings more failing. The university cannot sit on their high ground and watch these students struggle, especially if their number reaches a critical mass.
I am criticizing how AI progress is reported and discussed -- given how important this development is, accurate communication is even more important for the discussion.
I think you inferring my motivation for the rant and creating a strawman yourself.
I do agree that directing my rant at the generic "fans" is not productive. The article Tao wrote was a good example of communicating the result. I should direct my criticism at specific instances of bad communication, but not the general "fans".
It's really tiring that LLM fans will claim every progress as breakthrough and go into fantasy mode on what they can do afterwards.
This is a really good example of how to use the current capabilities of LLM to help research. The gist is that they turned math problems into problems for coding agents. This uses the current capabilities of LLM very well and should find more uses in other fields. I suspect the Alpha evolve system probably also has improvements over existing agents as well. AI is making steady and impressive process every year. But it's not helpful for either the proponents or the skeptics to exaggerate their capabilities.
https://youtu.be/LDSwP37y_W4?si=fMIsdQ2yjoiGChb6