Forever Young: how one molecule can lock plants in a youthful state (2025)(omnia.sas.upenn.edu)

116 points by bryanrasmussen 4 months ago | 67 comments

Claude Auth Is Down(claude.ai)

12 points by nabeards 2 months ago | 2 comments

AI sticker shock hits corporate America(axios.com)

117 points by 1vuio0pswjnm7 5 months ago | 99 comments

Deficient executive control in transformer attention(academic.oup.com)

33 points by derbOac 4 months ago | 11 comments

Communication by means of modulated Johnson noise(pnas.org)

53 points by austinallegro 1 month ago | 28 comments

Splash-free urinals: Design through physics and differential equations(academic.oup.com)

7 points by gradus_ad 1 month ago | 1 comments

What Problems to Solve (1966)(genius.cat-v.org)

456 points by jxmorris12 1 year ago | 54 comments

A 1966 letter from Richard Feynman to former student Koichi Mano advising him that worthwhile problems are ones you can actually solve, hosted on cat-v.org.

Watson Jr. memo about CDC 6600 (1963)(computerhistory.org)

51 points by mooreds 23 days ago | 30 comments

Computer History Museum exhibit page showing Thomas Watson Jr.'s August 1963 IBM memo about the Control Data CDC 6600 supercomputer.

Mechanochemistry of Molecular Motors [video](youtube.com)

11 points by surprisetalk 27 days ago | 2 comments

YouTube video of a Foresight Institute talk by Jonathon Howard on the mechanochemistry of molecular motors.

Jonathan Haidt: AI Is the 'Neutron Bomb for Education' [video](youtube.com)

22 points by ptrhvns 21 days ago | 39 comments

A YouTube video from The Atlantic's The Permanent Questions in which David Brooks interviews Jonathan Haidt about AI's impact on education.

RWKV: Reinventing RNNs for the Transformer Era(arxiv.org)

318 points by ianbutler 3 years ago | 164 comments

arXiv paper introducing RWKV, a model architecture combining Transformer-style parallel training with efficient RNN inference via linear attention.

Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory(arxiv.org)

412 points by Anon84 2 years ago | 132 comments

arXiv listing for a book by Jentzen, Kuckuck, and von Wurstemberger giving a mathematically rigorous introduction to deep learning methods, implementations, and theory.