SynSense develops mixed-signal neuromorphic processors that achieve ultra-low power consumption and low-latency performance for edge computing applications. Their technology addresses the challenges of high energy use and slow response times in AI systems, enabling efficient real-time processing across various domains such as robotics, smart homes, and autonomous driving.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional AI systems often suffer from high energy consumption and latency issues, particularly in edge computing applications where real-time processing and power efficiency are critical. These limitations hinder the deployment of AI in applications like robotics, smart homes, and autonomous driving.
Solution
SynSense provides mixed-signal neuromorphic processors designed to overcome the energy and latency bottlenecks of conventional AI. Their technology leverages brain-inspired computing principles to achieve ultra-low power consumption and low-latency performance, enabling efficient real-time processing at the edge. SynSense offers both application-specific integrated circuits (ASICs) and intellectual property (IP) blocks, along with full-stack application development services, to deliver complete neuromorphic solutions. Their approach integrates sensing and computing functionalities, providing a unique advantage in the neuromorphic technology landscape.
Target Audience
SynSense's primary customers include developers and manufacturers of robots, smart home devices, healthcare systems, smart toys, security systems, and autonomous vehicles seeking to enhance their products with low-power, low-latency AI capabilities.
Features
- Ultra-low power consumption, achieving 100x to 1000x savings compared to traditional solutions
- Ultra-low latency, enabling real-time processing with 10x to 100x faster response times
- Neuromorphic ASICs and IP blocks for custom hardware implementations
- Full-stack application development services, including algorithm design and software integration
- Solutions for smart vision, auditory processing, multimodal signal processing, and bio-signal processing
- Event-driven processing for efficient and privacy-preserving smart security systems
- Integrated sensory and computing capabilities for autonomous driving applications
- Software tools including Rockpool, Sinabs, and SAMNA for developing and deploying neuromorphic algorithms