Jev's Architecture Unmasked

Archer Hume · 3 weeks ago · 10 ● 19 sources

The author argues that Jev’s system avoids generating token-by-token confidence text and instead builds a shared transformer state that branches into multiple questions whose probabilities are read out directly as distributions. The key concrete detail is that Jev’s API claims to output probabilities in parallel rather than autoregressively generating by token. As a result, applications can route or decide using trained decision probabilities while shifting JSON formatting and other option handling to application code, with less repeated computation from re-processing the shared state for many questions.