Today we are announcing our new fully-asynchronous event-driven neuromorphic AI processor for ultra-low power, always-on, real-time applications.

DYNAP-CNN opens brand-new possibilities for dynamic vision processing, bringing event-based vision applications to power-constrained devices for the first time.

DYNAP-CNN is a 12mm2 chip, fabricated in 22nm technology, housing over 1 million spiking neurons and 4 million programmable parameters, with a scalable architecture optimally suited for implementing Convolutional Neural Networks. It is a first of its kind ASIC that brings the power of machine learning and the efficiency of event-driven neuromorphic computation together in one device. DYNAP-CNN is the most direct and power-efficient way of processing data generated by Event-Based and Dynamic Vision Sensors.

As a next-generation vision processing solution, DYNAP-CNN is 100–1000 times more power efficient than the state of the art, and delivers 10 times shorter latencies in real-time vision processing.

Those savings in energy mean that applications based on DYNAP-CNN can be always-on, and crunch data locally on battery powered, portable devices.

Computation in DYNAP-CNN is triggered directly by changes in the visual scene, without using a high-speed clock. Moving objects give rise to sequences of events, which are processed immediately by the processor. Since there is no notion of frames, DYNAP-CNN’s continuous computation enables ultra-low-latency of below 5ms. This represents at least a 10x improvement from the current deep learning solutions available in the market for real-time vision processing.

DYNAP-CNN Development Kits will be available in Q3 2019.

Zurich

Thurgauerstrasse 40, 8050 Zurich, Switzerland

Chengdu

No. 1999-8-5, Yizhou Avenue, Gaoxin District, Chengdu, Sichuan, PR China

Nanjing

No. 22-98, Dangui Road, Pukou District, Nanjing, PR China

Shanghai

No. 302, Building 21, ZJ AI Island, Pudong Xin District, Shanghai, PR China

Suzhou

No.398 Ruoshui Road, Suzhou Industrial Park, Suzhou City, Jiangsu Province, PR China

We don’t develop technologies or accept funding for military purposes.