We report a previously undocumented defect in how the Ollama runtime serves mxbai-embed-large, one of the most widely used open-source text embedding models: on every release from **v0.14.
Pygmalion's notebook *artificial time* sketches an ambitious unified theory of machine cognition: meaning is made of relations between words; words are agreements on labels; context is the base relation from which all others draw meaning; information is carried by *infons* in *situations*; memory is a recursion indexed by an "artificial time"; words map bijectively to reconfigurable "VHDL-style" neural blocks; and a topos-level layer reasons about those blocks. We do two things with it.
Conventional operating systems treat the CPU as the brain and the GPU as an accelerator, and treat AI as something bolted on through serialization layers (text, JSON, tool-call schemas). For workloads where both **predictable latency under load** and **first-class local AI** matter — defense, aerospace, industrial control, medical devices, autonomous systems — neither inversion is paid for, but both costs are felt: GPU-resident models thrash against CPU-resident schedulers, and every round trip through the OS/AI boundary costs an embed/decode pair that drops information and adds jitter.