zeekay d10de53d99 Add mechanism and training papers; ground the series in what ships ...

Two papers were missing and four understated what we already run.

mechanism  the Hamiltonian market maker: price as position under a
           regime-dependent anharmonic potential, symplectic so it does not
           drift on noise, regime recovered as the latent state of a hidden
           Markov model, per-resource states whose prices never cross, one-bit
           tenant preference deltas, quotes deterministic given job and market.
           States plainly why a constant-product curve cannot express
           perishability, deadline pressure or scarcity convexity.
training   training and data as market workloads over open weights: the
           tradable units and their properties, gradient verification, the
           four confidential-compute tiers with local attestation, and
           train-without-transfer for weights and corpora that may not be
           copied.

soundness  attested execution rewritten. At a few percent overhead it is the
           default for everything byte equality cannot reach, not a curiosity;
           paired with algebraic spot-checks it beats replication on both cost
           and coverage.
clearing   the pricing layer and the learned per-request router are existing
           systems, not proposals; open weights are what a provider network can
           actually schedule.
residency  the shared-object-plus-tiny-delta pattern appears at the pricing
           layer too, and where the analogy stops is the interesting part.
surplus    verification for the nondeterministic majority, and training and
           data, as sized surplus lines; three additions to the risk register.

2026-08-26 13:20:12 -07:00

227 KiB

Raw Permalink History

View Raw