Intellicortex
Intellicortex
A new class of AI architectures built for predictable compute, continual learning, and scalable intelligence.
Modern AI systems grow by scaling parameters, driving inference and training costs to unsustainable levels.
Dense models forget prior knowledge and require expensive retraining whenever new data arrives.
Once deployed, models adapt poorly to changing environments and depend on massive centralized infrastructure.
Bound computation by design to ensure predictable performance, bounded latency and energy‑proportional scaling.
Enable learning through structural adaptation rather than costly retraining, supporting continual improvement.
Separate stable cognitive priors from adaptive memory so knowledge persists while memory can change rapidly.
Generate connectivity on demand using compact codebooks and deterministic rules, eliminating memory explosion.
A compute-governed neural architecture that enforces hard compute budgets while enabling continual learning through structural adaptation.
Technical Deep-DiveA scalable intelligence platform built on SPARSITRON™ that provides cost‑governed inference, adaptive agents and integration with dense AI models.