Research areas
Research
Sparse, routed and resource-aware AI architecture.
NeuroForge explores intelligence systems that can be profiled, extended, benchmarked and deployed under realistic compute constraints.
Research thesis
AI architecture should be measurable, extensible and resource-aware.
NeuroForge studies systems that expose enough structure to test what changed, why it changed and which subsystem carried the work.
ERAIS is the current research programme exploring routed, modular and resource-aware intelligence-system architecture with formal evaluation and proof surfaces.
Sparse routing
Route work to relevant modules rather than paying dense activation cost for every input.
Continual extension
Explore capability growth without uncontrolled interference with existing behaviour.
Local-first systems
Support efficient, auditable systems that can operate closer to their users and data.
Evaluation, collaboration and funding
NeuroForge is preparing controlled technical review and external evaluation pathways.
For research discussion, evaluation or funding enquiries, contact Lloyd Handyside directly.