Research pillars
Ace Labs presents NeuroForge
Efficient intelligence systems, engineered from evidence.
NeuroForge develops sparse, routed and resource-aware AI architecture research with an emphasis on measurable behaviour, repeatable evaluation and practical deployment constraints.
Why NeuroForge exists
Efficient AI requires stronger evidence, not louder claims.
Modern AI systems are often expensive to run, difficult to audit and difficult to compare cleanly. NeuroForge approaches AI architecture as an experimental system: isolate variables, run controlled changes, measure outcomes and refine from evidence.
The current research direction focuses on routed and modular systems that aim to activate relevant capability for a given task rather than treating dense activation as the default answer to every problem.
Efficient by design
Sparse routing and modular activation are explored as first principles for reducing unnecessary computation.
Learn moreScientific by habit
Experiments use controls, manifests, repeated tests and failure analysis to keep claims grounded.
Learn moreAgent-readable
Clean HTML, JSON-LD, Markdown context, llms.txt and a machine-readable manifest support accurate technical discovery.
Learn moreEvaluation, collaboration and funding
NeuroForge is preparing controlled technical review and external evaluation pathways.
For research discussion, evaluation or funding enquiries, contact Lloyd Handyside directly.