[No AI was used in composing this blog post.]
I’ve been trying to get back to the blog recently. But every time I plan to write a blog post, something happens that requires my attention and adds to the list of items I should be writing about.
I’ve decided that the best I can do, for now, is to summarize some of the key stories that have been on my radar. Because I’m covering so many topics so briefly, the chance of an error is pretty high; please let me know if you spot inaccuracies. Normally I try to be super-careful, but today I’m prioritizing conveying the sense of things rather than getting every detail right. Moreover, a lot of what follows is half-baked opinion; things are happening way too fast for me to be sure that my thinking is clear and correct, so you should interpret this post in that context.
The overarching news, aside from the 2026 physics Nobel Prize is what you’ve heard: artificial intelligence (AI) is transforming mathematics and high-energy theoretical physics, no question. That said, what is reported in the media about this is usually wrong in key details, and almost always wildly overstates what’s been accomplished. Nevertheless, the advances in AI models in the last couple of months are historic and transformative, and there is every reason to expect this to accelerate. For people like me, 2027 will surely be very different from autumn 2026, which in turn barely resembles spring 2026.
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