A deep dive into Percepta's breakthrough: shrinking memory bottlenecks with 2D attention, enabling a native virtual computer inside a language model. We unpack convex-hull memory queries, a WebAssembly interpreter running in vanilla PyTorch weights, and what this means for how models compute, reason, and potentially compile software—redefining the future of AI tooling and problem solving.

Note:  This podcast was AI-generated, and sometimes AI can make mistakes.  Please double-check any critical information.

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