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- CS 312: Deep Learning Alchemy (cs.stanford.edu)
- Stripe acquires Clerky (twitter.com)
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Diffusion LLMs (dLLMs) seemed so promising a year ago, but I don't see much about them now. What happened?
- Gamgee (ycombinator.com)
- A Workaphile's Apology (moalquraishi.wordpress.com)
- The Pedagogy Behind the Studio (gail.wharton.upenn.edu)
- Macos27.kimi.page (macos27.kimi.page)
- Decoy Font (mixfont.com)
- Capable (hypercapable.vercel.app)
- Baby Pictures (reddit.com)
- The Unreasonable Redundancy of Nature's Protein Folds (research.ligo.bio)
- UMA Playground (aidemos.atmeta.com)
- The Unmet Needs Index (convoke.bio)
- Learning to Discover at Test Time (test-time-training.github.io)
- ProteinView (github.com)
- Welcome to Actual Computer (actual.inc)
- Resolution Challenge (rico.ibs.fr)
- AI has the worst sales pitch I've ever seen (noahpinion.blog)
- TurboQuant: Redefining AI efficiency with extreme compression (research.google)
- I'm going to cure my girlfriend's brain tumor (andrewjrod.substack.com)
- ClaudePad (github.com)
- Boltz Bio Manifesto (boltz.bio)
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Cerebras' wafer-scale chips seem like the outperform any of Nvidia's solutions for inference workloads. Since most people run inference in the cloud anyway, why aren't more datacenters being built with this technology…