Independent research on neuromorphic computing, continual learning, and bio-plausible AI architectures. No consensus. No committees. Just experiments.
A spiking neural network architecture that solves catastrophic forgetting through Hebbian plasticity rules. No backpropagation. No gradient descent. Local learning only — the way brains actually work.
Industrial simulation benchmarking MorphoCore vs traditional AI. 3.3× faster reaction time. 50× lower operational cost.
Robots learning multiple motor behaviors sequentially without forgetting previous skills. Purely local learning rules.
Brain simulation integrated with morphological expression via Gray-Scott reaction-diffusion patterns. Unlimited creative expression for AI systems.
MorphoCore learning 120,000 tokens from literature and chess patterns sequentially — zero catastrophic forgetting.
SynapticLab is one independent researcher,
building bio-plausible AI from first principles.
No institution. No committee. No consensus required.
Each POC is a live experiment — published as-is,
with raw numbers and honest conclusions.