Foundational AI · Physical World Applications
Like LLMs but for the physical world around you.
The Gap
Existing AI technology does not meet the growing demand for autonomy and robustness. Most companies focus on building solutions around language, like multimodal LLMs.
LLMs are successful in their lane — but language is not the right core to learn about and generalize in the world.
Perception is more fundamental
than linear narration.
The Solution
With a 10-year head start, Blindspot Labs has a viable and unique approach: a perception processor — an architecture built from the ground up to understand, generalize, and act in the physical world.
Unlike typical end-to-end and deep networks, our SHARP networks have special recurrent connectivity, spreading activity throughout and across the network. This heterarchical connectivity enables capabilities beyond current deep networks. It models the world at multiple scales, and naturally handles sensors at different rates — even rolling shutters.
The SHARP network is a novel design
with capabilities beyond current deep networks
Our Advantage
It started inside a DARPA seed program, spotted early by a handful of people who saw what it could become. Years of development later, our solution is ready to redefine robotics and AI. The team backed by a track record of real-world wins and a grounded perspective no one else has.
Applications
Autonomous systems powered by our solution understand and navigate the physical world — with native spatial and temporal perception rather than learned text priors.
Real-time intelligence at the point of action — no cloud dependency, no latency, full autonomy in constrained environments.
Perception can be local or span a broad array of sensors external to the autonomous system — expanding the definition of perception, adaptation, and situational awareness.
Today's AI enables only a small slice
of what will become possible
with a perception processor.