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Most AI products forget. Cogweald is designed to remember.

Many AI demos feel intelligent until you ask the same question the next day. The problem is often not the model. The product simply has no durable world state. The conversation ends, the memory ends with it, and the next request starts from a blank page. Cogweald takes a different approach: put AI inside a world that keeps running. Characters have state. Events leave consequences. Unresolved…

We haven't written up this one. Dev.to has the full story — the link below goes straight to it.

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I just did something my AI agents couldn't

It is funny how things work out. You can let AI tools try to fix a code problem for days, but nothing works until you finally step in and do it yourself.

  • Attempted to organize ESP-IDF project using AI tools
  • AI suggestions caused numerous errors in code
  • Switching to GitHub Copilot and manual fixes resolved issue

[Insight] Why Nvidia Is Bringing Rival AI Chips Into Its Ecosystem

U.S. AI chip startup d-Matrix said on Sept. 10 that its next-generation Raptor XPU will connect directly to Nvidia MGX rack-scale infrastructure through NVLink Fusion.

  • Nvidia integrates rival AI chips, d-Matrix's Raptor XPU, into MGX infrastructure.
  • Raptor's memory-centric architecture reduces data movement bottlenecks in AI inference.
  • Partnership enables Nvidia's GPUs and Raptor to work together on AI inference stages.

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