POLYN Technology, an innovative developer of application-specific neuromorphic analog signal-processing (NASP™) chips, has published a white paper that explores a new paradigm combining the capabilities of neural networks and deterministic signal- processing systems.

The Deterministic Responsive Computing for Physical AI Systems white paper examines how this paradigm can bridge the gap between traditional signal processing and neural inference through the use of fixed-hardware neural network implementations. POLYN’s NASP technology is a particular ultra-low-power, low-latency implementation of deterministic responsive computing (DRC).

“Deterministic responsive computing is the latest addition to Physical AI architecture that combines neural inference with fixed execution structures and time-bounded operational behavior,” said Dmitry Godovsky, Chief Scientist of POLYN. “This paradigm introduces a dedicated computational layer positioned between sensing and high-level cognition.”

The potential benefits of DRC are addressed in detail in the white paper in areas such as humanoid robotic motion detection, battery safety monitoring, and tire-road friction assessments. All these applications and more could be enhanced by DRC.

The white paper can be accessed at POLYN’s website.