post-transformer

interactive, sub-16ms vector explainer built for the DataForge 2026 Pathway Track.It proves why classical State Space Models suffer exponential associative forgetting ($\rho(A)^L$) and visualizes how Pathway's Dragon Hatchling (BDH) synaptic plasticity and BDH CQ continuous latent reasoning eliminate interference without KV-cache explosion.

Building intelligence from advanced dynamics

Interactive explainer: BDH's attention has no softmax, so it is exactly a Hebbian synaptic memory — one fixed-size matrix written once per token. Run both forms, watch them agree to 1e-16, then break it with one toggle. DataForge 2026, Pathway track.

Energy First Architecture (EFA): a post-transformer, on-device, energy-based architecture for Physical AI. Charlot Lab · Institute for Physical AI @ BMI.