https://www.complexsystemspodcast.com/episodes/the-economics-of-putting-germicidal-light-in-every-room/ why can’t you just put far-UVC everywhere? well. there’s no secret catch. there’s no real safety risk. there’s no technological hurdle. it’s not illegal. it’s not unpopular. the barrier is just Marketing. Most people haven’t heard of it. Most people aren’t sure if it’s worth $500. By their own admission, the guys making it don’t think it’s a slam-dunk good buy for a household (though I have one), it’s more that it would probably reduce illness in high-traffic public indoor spaces, and we don’t have the data yet on how much illness it reduces.
there’s some kind of lesson in this. “why isn’t it everywhere yet? it’s useful! what’s the problem?” no, there’s no problem. it’s just that millions of people people don’t instantly simultaneously realize that something is probably a good idea and shell out $500 for it. aka, there’s a reason sales teams exist!
https://www.lesswrong.com/posts/mkbGjzxD8d8XqKHzA wait, you can just...Do SVD To It? where “it” is the transformer’s own weight matrix??? and this gives interpretable, semantically meaningful clusters in token embedding space? how did i not know this.
this is the predecessor to SAEs. the point of SAEs is you can get more features with a sparse overcomplete basis. Just Do SVD To It can’t give you more vectors than the rank of the matrix.
also, it’s more of an indication of average behavior than what’s activating in response to a particular input. that’s why we need circuits.
https://arxiv.org/pdf/2512.12469 method of concept embedding and deletion by dictating the geometry of concept embedding during training, in this case, distributing colors on the unit sphere. seems like a legitimate idea but still at the proof of concept stage (not even tried on a lanugage transformer yet)
links 8/7/26: https://roamresearch.com/#/app/srcpublic/page/08-07-2026
https://www.lesswrong.com/posts/AfoGGrJfuNzofpzWL/models-may-behave-differently-in-graded-episodes-a-tirade nostalgebraist on “eval awareness.” everything about this is true and good.
https://www.complexsystemspodcast.com/episodes/the-economics-of-putting-germicidal-light-in-every-room/ why can’t you just put far-UVC everywhere? well. there’s no secret catch. there’s no real safety risk. there’s no technological hurdle. it’s not illegal. it’s not unpopular. the barrier is just Marketing. Most people haven’t heard of it. Most people aren’t sure if it’s worth $500. By their own admission, the guys making it don’t think it’s a slam-dunk good buy for a household (though I have one), it’s more that it would probably reduce illness in high-traffic public indoor spaces, and we don’t have the data yet on how much illness it reduces.
there’s some kind of lesson in this. “why isn’t it everywhere yet? it’s useful! what’s the problem?” no, there’s no problem. it’s just that millions of people people don’t instantly simultaneously realize that something is probably a good idea and shell out $500 for it. aka, there’s a reason sales teams exist!
https://arxiv.org/pdf/2603.20994 game theory formalism about AIs that disobey the user to fulfill an ethical imperative
https://www.lesswrong.com/posts/mkbGjzxD8d8XqKHzA wait, you can just...Do SVD To It? where “it” is the transformer’s own weight matrix??? and this gives interpretable, semantically meaningful clusters in token embedding space? how did i not know this.
this is the predecessor to SAEs. the point of SAEs is you can get more features with a sparse overcomplete basis. Just Do SVD To It can’t give you more vectors than the rank of the matrix.
also, it’s more of an indication of average behavior than what’s activating in response to a particular input. that’s why we need circuits.
https://arxiv.org/pdf/2512.12469 method of concept embedding and deletion by dictating the geometry of concept embedding during training, in this case, distributing colors on the unit sphere. seems like a legitimate idea but still at the proof of concept stage (not even tried on a lanugage transformer yet)
https://biodynai.com/ mechinterp for bio foundation models. i’m intrigued.
https://warwick.ac.uk/fac/sci/statistics/news/probai-scaling-laws-2026/programme/blake_tutorial.pdf tutorial on dynamical mean field theory