“Does AI Progress Have a Speed Limit?” links to an April 2025 dialogue between Ajeya Cotra and Arvind Narayanan. Perhaps you wanted to link the 2023 dialogue between Tamay and Matt Clancy, also on Asterisk?
Actually I did want to link to the debate between Ajeya and Narayanan. As part of working on the website I wanted to try out various AI tools since I haven’t been coding outside the OpenAI codebase for a while, and I might have gone overboard :)
Students are continuing to post lecture notes on the AI safety course, and I am posting videos on youtube. Students experiments are also posted with the lecture notes: I’ve been learning a lot from them!
Posted our homework zero on the CS 2881 website, along with video and slides of last lecture and pre-reading for tomorrow’s lecture. (Homework zero was required to submit to apply to the course.)
A blog post on the first lecture of CS 2881r, as well as another blog on the student experiment by @Valerio Pepe , are now posted . See the CS2881r tag for all of these
Got my copy of ’If anyone builds it everyone dies” and read up to chapter 4 this morning but now have to get to work.. I might write a proper review after I finish it if I get the time. So far, my favorite parable was the professor saying that they trained an AI to be a great chess player and do anything to win, but “there was no wantingness in there, only copper and sand.”
I agree that we are training systems to achieve objectives, and the question of whether they “want” to achieve them or don’t is a bit meaningless since they will defintiely act as if they do.
I find the comparisons of the training process to evolution less compelling, but to quote Fermat, a full discussion of where I see the differences between AI training and evolution would require more than a quick take...
First lecture for CS 2881 is online https://boazbk.github.io/mltheoryseminar/ + prereading for next lecture.
Students will be posting blog posts here with lecture summaries as well.
Thank you for doing this!
Btw I assigned AI 2027 as pre reading for the first lecture! (As well as “AI as a normal technology “ and the METR paper on doubling time for tasks.)
Nice. If you get a chance I’d love to hear what the students think about all of the above.
The Arbital link (Yudkowsky, E. – “AGI Take-off Speeds” (Arbital 2016)) in there is dead, I briefly looked at the LW wiki to try find the page but didn’t see it. @Ruby?
Thanks—dropped it for now
This looks great! Thanks for making the videos public.
Any chance the homework assignments/experiments can be made public?
Posted HW0 now and will post future ones also!
Neat!
“Does AI Progress Have a Speed Limit?” links to an April 2025 dialogue between Ajeya Cotra and Arvind Narayanan. Perhaps you wanted to link the 2023 dialogue between Tamay and Matt Clancy, also on Asterisk?
Actually I did want to link to the debate between Ajeya and Narayanan. As part of working on the website I wanted to try out various AI tools since I haven’t been coding outside the OpenAI codebase for a while, and I might have gone overboard :)
Students are continuing to post lecture notes on the AI safety course, and I am posting videos on youtube. Students experiments are also posted with the lecture notes: I’ve been learning a lot from them!
Posted our homework zero on the CS 2881 website, along with video and slides of last lecture and pre-reading for tomorrow’s lecture. (Homework zero was required to submit to apply to the course.)
https://boazbk.github.io/mltheoryseminar/
Video is on youtube too
Our paper on scheming with Appolo is now on the arxiv. Wrote up a twitter thread with some of my takes on it: https://threadreaderapp.com/thread/1970486320414802296.html
A blog post on the first lecture of CS 2881r, as well as another blog on the student experiment by @Valerio Pepe , are now posted . See the CS2881r tag for all of these
https://www.lesswrong.com/w/cs-2881r
The video for the second lecture is also now posted on YouTube
Wrote one long comment in my non review of IABIED as response to a bunch of other comments.
Got my copy of ’If anyone builds it everyone dies” and read up to chapter 4 this morning but now have to get to work.. I might write a proper review after I finish it if I get the time. So far, my favorite parable was the professor saying that they trained an AI to be a great chess player and do anything to win, but “there was no wantingness in there, only copper and sand.”
I agree that we are training systems to achieve objectives, and the question of whether they “want” to achieve them or don’t is a bit meaningless since they will defintiely act as if they do.
I find the comparisons of the training process to evolution less compelling, but to quote Fermat, a full discussion of where I see the differences between AI training and evolution would require more than a quick take...