Prophesee teams for event driven vision in IoT

November 28, 2021 // By Peter Clarke
Prophesee, SynSense form vision computing partnership
French event-driven sensor designer Prophesee is working with swiss neuromorphic computing startup SynSense on a single chip design for the Internet of Things (IoT).

The two European companies have strong Chinese connections and have formed a partnership to develop combination vision computing chips and subsystems.

The partnership will combine SynSense's spiking neural network, known as Dynap-CNN, with Prophesee's event-triggered Metavision image sensors in a single chip. The partnership is focused on developing a set of low-cost, low energy consumption vision computing systems for manufacture at high volume. The combination will produce an implementation similar to a biological vision system that be co-marketed by both companies and commercialized by SynSense for IoT and smart-home detection and gesture control applications.

The Prophesee sensor has a number of advantages over conventional imaging as it records changes in the scene rather than recording the entire scene at regular intervals. This gives better low light response and dynamic range, reduced data generation and lower bandwidth and processing requirements and higher temporal resolution.

However this needs a different machine learning framework, so the partnership will address the design, development, manufacturing and commercialization of the combined neuromorphic technology, including sensors, processing solutions, software and solutions to enable a broad range of applications.

"A recent report by Yole Developpement forecasts that neuromorphic computing and sensing will represent between 15 and 20 percent of total AI computing revenue in 2035, about a roughly $20 billion market." said Ning Qiao, CEO of SynSense.

Although both companies are European they both have Chinese involvement. SynSense was founded as a spin out from the Institute of Neuroinformatics at the University of Zurich in March 2017 by Qiao. He gained his PhD at Tsinghua University, Beijing and spent time at the prestigious Institute of Microelectronics at the Chinese Academy of Sciences.

Next: Chinese funding

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