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NOTA’s deep learning model compression technology allows models to be stored individually on small edge devices without affecting the performance. Compared to large AI models, our on-device AI technology incurs only 20% of the previous cost and speeds up inference and predictions by 70%. Our compression removes latency, server/network cost, and privacy problems, while still achieving state-of-the-art performance at object detection, identification, and tracking. Clients can benefit from our stand-alone AI products at a lower cost, faster inference, and no privacy concerns.
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