NeuroGenesys.
Milestones

The frontier, measured.

Research claims are cheap; measurements are not. These are the numbers our programs stand behind — modelled advantages, exact factorizations, honest negative results — published and reproducible.

Lab Metrics

Numbers that matter.

11.8×

Modelled Analog Compute Advantage

Analog in-memory compute holds a context-independent 11.8× decode advantage for static-weight sequence models — modelled in our cost-model campaign, with the exact boundary published.

98.7%

Frozen-Expert Accuracy, Split-MNIST

Freeze one small expert per task and each is near-perfect. All of class-incremental difficulty is selection — confirmed on Split-CIFAR-100 in November, where routing error grew from 0.53 to 0.79 as tasks went from 5 to 20.

3000×

Optical Precision Robustness

Random-feature optical inference tolerates roughly 3000× the precision degradation that collapses a conventional matmul — one of two genuine optical advantages our falsification study confirmed.

70+

Pre-Registered Experiments

Run-once, seeded, kill-criterion-first: the falsification campaign behind our analog compute design rule — every headline claim traceable to a numbered experiment.

Research Output

One lab. Many frontiers.

40

Open Research Publications

Preprints, syntheses, defensive publications, and negative-results studies — analog compute, continual learning, test-time compute, photonic inference, cognition, and mathematics. Experiments run once from fixed seeds.

Where The Work Goes

  • Models: forgetting & verification24 papers
  • Silicon: analog & optical compute10 papers
  • Foundations: cognition & mathematics6 papers

*Every program shares the same loop: neuroscience informs the models, and what the models need shapes the silicon we study.

2026 Milestones

  • Wave-cognition falsification publishedJun
  • Verifier exploitability draft, since supersededJun
  • Spectral response theorem confirmedJul
  • Analog compute design rule publishedJul
  • Self-critique correlation measuredSep
  • Public findings ledger openedNov
  • Genesys program and pre-registered testsNov
  • Real-judge Best-of-N: kill criteria triggeredNov
  • Forgetting as selection confirmed on CIFAR-100Nov
Lab Status: All Programs ActiveView All Publications
Field Notes

Restoring speech
and movement

Bandwidth measured
in words

A decade ago, brain-computer interfaces moved cursors. The field's best speech neuroprostheses now decode attempted speech at conversational rates — progress we track, with sources, in our field notes.

78 wpm

Best Published Decode (2023)

4,096

Electrode Field Record (2024)

Air-gapped
frontier evals.

Our published standard: any frontier capability increase runs its dangerous-capability evaluations inside physically isolated sandboxes — no network path out until oversight signs off.

Our Standard — Before Any Release

Drawn from every
discipline

  • NeuroscienceField notes
  • Machine LearningVerification
  • Silicon EngineeringCost models
  • Ethics & PolicyNeurorights
Field Notes

Neuromorphic
edge intelligence

The SynapseOne program: always-on, event-driven inference for implants, wearables, and robots — studied against our published analog compute design rules.

One SDK.
Every frontier.

The developer surface the Genesys program is building toward: models, decoders, and silicon targets behind one SDK — from notebook to implant. In design now.

$ npm install @neurogenesys/sdk
→ not yet published — the SDK is in design

Leadership

A word from the founder — on why the brain is the blueprint, and why the next decade of intelligence will be built here.

"The brain is the universe's only proof that general intelligence is possible. We treat it as the blueprint."

From cortical interfaces to photonic silicon, every program at NeuroGenesys exists to answer one question: how does intelligence arise — and how do we build it safely.

Will Schulz

Will Schulz

Founder, NeuroGenesys • AW3 Technology