Syntiant Corp., a leader in delivering end-to-end edge AI solutions for always-on applications, announced the availability of a full suite of pre-trained and customizable deep learning models for computer vision applications.
Capable of running on most hardware platforms including CPUs, GPUs, DSPs, FPGAs, and ASICs, Syntiant’s edge AI algorithms are being deployed in security and IP cameras, 360/VR cameras, video doorbells, video conferencing systems and other use cases.
“We are building upon our leadership position in voice and audio by offering scores of off-the-shelf machine learning models for edge-based image and vision applications,” said Kurt Busch, CEO of Syntiant. “These hardware agnostic models can be easily customized and work on a wide range of SOCs, including our own NDP200, which brings together the best of both worlds into a powerful, compact, highly efficient turnkey solution.”
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Syntiant’s turnkey solution provides the data, tools and training for quick and easy edge deployments across the following industries:
- Smart home (intrusion detection, doorbells, face recognition)
- Personal Devices (face recognition, gesture recognition, noise suppression)
- Automotive (vehicle identification, theft detection, driver awareness)
- Government (national security applications for air, sea, land and space)
- Industrial (object identification, condition-based monitoring, analytics)
“Software service revenue for edge AI is expected to grow to over five billion in 2027, with most of that derived from computer vision,” said Lian Jye Su, analyst at ABI Research. “New models and use cases are emerging every month. Furthermore, end users need to integrate computer vision into end devices with various form factors, processing power, and battery consumption. Having developer-friendly and production-grade edge AI software allows quick onboarding and development of edge AI-based computer vision models. As a result, enterprises can overcome the lack of edge AI expertise and focus on operation.”
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