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  1. Diffusion LLMs (dLLMs) seemed so promising a year ago, but I don't see much about them now. What happened?

  2. Gamgee (ycombinator.com)
  3. A Workaphile's Apology (moalquraishi.wordpress.com)
  4. The Pedagogy Behind the Studio (gail.wharton.upenn.edu)
  5. Macos27.kimi.page (macos27.kimi.page)
  6. Decoy Font (mixfont.com)
  7. Capable (hypercapable.vercel.app)
  8. Baby Pictures (reddit.com)
  9. UMA Playground (aidemos.atmeta.com)
  10. The Unmet Needs Index (convoke.bio)
  11. Learning to Discover at Test Time (test-time-training.github.io)
  12. ProteinView (github.com)
  13. Resolution Challenge (rico.ibs.fr)
  14. ClaudePad (github.com)
  15. 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…