Excerpt: “The fact that it’s been 3 years since ChatGPT first launched, and you’ve only just now managed to make it obey this simple requirement, says a lot about how little control you have over it, and your understanding of its inner workings,” wrote one X user in a reply. “Not a good sign for the future.”
I can't find the site that I read a while ago, it was very similar to the myticker.com site that was posted the other day for heart disease but focused on myopia.
It's difficult for artificial light to compete with full-spectrum natural daylight from an infinitely distant light source (sun). See previous attempts at sunlight simulation indoors.
Excerpt:
But here’s a reason why other people might care. This is the first paper I’ve ever put out for which a key technical step in the proof of the main result came from AI—specifically, from GPT5-Thinking.
It can't offer solutions, it can offer cribbed patterns from the training corpus (more specifically some fuzzy superposition of symbol combinations) that apply in some specific context. It's not clear why Aaronson is constantly hyping this stuff b/c it seems like he is much more rigorous in his regular work than when he is making grand proclamations about some impending singularity wherein everyone just asks the computer the right questions to get the right answers.
More generally LLMs are bad at exhaustivity: asking "give me all stuff matching a given property" almost always fails and provide at best a subset.
If possible in the context, the way to go is to ask for a piece of code processing the data to provide exhaustivity. This method have at least some chance to succeed.
My Roomba is just crap compared with DJI's. I'm not surprised they went bankrupt.
a ROMO video https://youtu.be/Iv7BYURURRI?si=gfaPPiFpEMj1SVaT