Research
We explore how event-driven SNNs can replace transformer attention for low-power edge inference, achieving competitive performance at a fraction of the energy cost.
Custom silicon designed natively for SNN workloads. Here's what we're building, why conventional GPUs are inadequate for brain-inspired AI, and the technical roadmap ahead.
Bigger isn't always better. We make the case for small, efficient, private AI — and why sub-billion parameter models are the future of personal computing.