Our nation’s most demanding applications require performance and accuracy at the speed of light. Missions like Automatic Target Recognition (ATR), Hypersonic Vehicle Detection, and Autonomous Navigation all require real-time processing and inferencing on countless high bandwidth multi-phenomena sensors in parallel, rendering modern Machine Learning (ML) processors like CPUs, TPUs, and GPUs inert.
Bascom Hunter specializes in leveraging Silicon Photonics to offload the most compute-intensive tasks in ML, like Matrix Vector Multiplication (MVM). By leveraging analog optical processing, our processors avoid the classic electronic bottlenecks to achieve classification latencies as low as 200 picoseconds; translating to 0.16 Terra Multiply-Accumulate operations per second.
Additionally, in collaboration with Princeton University’s Lightwave Lab, Bascom Hunter is developing all-optical Photonic Neural Networks. These systems leverage the intrinsic strengths of optical devices and interconnects to create a physical computing solution to ML requirements. These cutting-edge systems enable sub-nanosecond inference on RF signals, 10s of GHz in bandwidth, with tremendous power saving compared to conventional ML hardware.