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DeepMind’s roughly six-minute overview video, “Generating novel scientific hypotheses with Co-Scientist,” opens not with a product demo but with a confession from scientists: the firehose of new literature has long since outpaced the humans trying to drink from it. One researcher describes having “hundreds of Chrome tabs and papers open.” Another says the amount of knowledge needed to stay at the frontier of a field now doubles roughly every two months....

Weekly Paper Notes — one of the top picks from the May 17–23, 2026 CS paper digest. Area: AI / ML. Authors: Ali Hatamizadeh, Yejin Choi, Jan Kautz (NVIDIA) arXiv: 2605.22791 · PDF · Code TL;DR Linear-attention models compress an unbounded history into a fixed-size recurrent state, but their active edit — the operation that overwrites stale associations with new ones — has historically been controlled by a single scalar gate that decides both how much old content to erase and how much new content to write....

Weekly Video Notes — a short article distilling one talk from the weekly digest. Source video and key frames are embedded throughout. 📜 Classic of the Week. This week’s digest re-surfaces a 2023 classic: Andrej Karpathy’s “Let’s build GPT: from scratch, in code, spelled out.” Three years later it is still, hands down, the clearest single resource for understanding what is actually happening inside a transformer. If you have never sat with it end-to-end, this is your nudge....

Weekly Video Notes — a short article distilling one talk from the weekly digest. Source video and key frames are embedded throughout. Pathway staged something unusual: a panel debate, framed as a literal boxing match, on whether the transformer is the final architecture of the AI era — or whether we are already living through the dawn of a post-transformer one. In the blue corner, defending the belt: Łukasz Kaiser, co-author of Attention Is All You Need and one of the minds behind GPT-4 and o-series reasoning models at OpenAI....