Links
Twitter @dpaleka
AI moves fast. It is hard to overstate how just new everything in machine learning is. Twitter is the best way to know what happens, and the best way to show other people what you create.
Furthermore, it’s a good way to connect with people who could make great collaborators or friends. You should have Twitter.
Of course, Twitter is social media, hence it is full of bad actors and bots. I decided upon two simple rules to make it more bearable: (1) mute people who post things you don’t want to waste attention on; (2) block trolls before they interact with your tweets.
Do that liberally, as your time is precious.
Philosophy and technology
- Nat Friedman
- Paul Graham
- Sam Altman
- Favorites: Moore’s law for everything, how to be successful
- Alexey Guzey
- Favorites: ideas matter, making friends over the internet
- dynomight
- Favorites: being managed, historical analogies for LLMs
- Ben Kuhn
- Favorites: searching for outliers, staring into the abyss
- Evan Conrad
- Favorites: moral competence
- Elad Gil
- Favorites: technology vs species threats, get shit done
- Patrick Collison
Academia
Machine learning online resources
Research group blogs
AI/ML researchers
AI security and safety
Applied machine learning
- Eric Jang
- Favorites: just ask for generalization, reviewing papers, rome
- Zhendong Wang
- John Schulman
- Favorites: an opinionated guide to ML research
- Andrej Karpathy
- Davis Blalock
- yacine
- Patrick Kidger
- Favorites: solo PhD advice
Machine learning theory
If you have (or have read) a cool site along these lines, feel free to send me a link.
Misc
Out of distribution
- Bits About Money by Patrick McKenzie
- Matt Levine
- Milan Cvitkovic
- Bartosz Ciechanowski
- Austin Z. Henley
- gwern.net
- Guzey’s Best of Twitter
- ACoUP
- Favorites: the LOTR series, steppe nomads
- Matt Lakeman
- Favorites: all the travel writing
Evergreen links
Other lists of links
Remarks
I do not endorse any of the sites above, and especially any people behind those.
A site being here means that it’s either interesting or important. Many things that are important are not good, and many interesting things don’t turn out to be true or useful.