There was a recent link on HN about Tao explaining Six Essential Mathematical Concepts https://news.ycombinator.com/item?id=49503521

Here's an excerpt of the video where he explains his idea: https://www.youtube.com/watch?v=svl_1upFpQo

My summary: Science is like a hike. You have a general sense of what direction you want to go. You explore things along the way. You might make wrong turns but might also discover something new and interesting. While on your journey, you might spot new mountains or waterfalls or other vistas that look like they might be good to explore.

In contrast, AI is like taking a helicopter to your destination. Yes you got there quickly, but you missed a lot on the way.

Related, Tao later talks about the pipeline. It used to be that seminal proofs were rare, so there was lots of time for the community to review them, process them, share them, and summarize them in textbooks. Nowadays, AI helps a lot with generating more proofs, but not so much with the other parts of the pipeline.

Tao also explains the math pipeline issue in his talk at the International Congress of Mathematicians, also shared on HN last month: https://news.ycombinator.com/item?id=49056620

My overall take: Tao is very thoughtful and insightful about progress in AI and math, and about what the tradeoffs are. We're seeing similar problems in computer science (my field), where conferences are now getting over 10x the number of submitted papers over just a few years ago (not an exaggeration). It's straining the research community in ability to review, understand, and present the papers.