Xnor.ai Website Review

Announcing the first Edge AI Summit, December 2018, in San Francisco more info & sign up Integrate AI software functionality like computer vision, speech recognition or almost any other machine learning functionality into your products, making them smart. Xnor AI models are designed to run in resource constrained environments and are performance optimized on easily run locally, even on battery-operated everyday products. Our binary neural networks are up to 10x faster, 30x more power efficient, and need 15x less memory than traditional de*p learning models on commodity CPUs. Xnor binarized models run on hardware from the simplest ARM MCUs to the most powerful x86 server CPUs, and can take advantage of performance acceleration hardware like GPUs, DSPs, and custom AI accelerators, including FPGAs. 10X Faster ------------------------- 30X More power efficient ------------------------- 15X Less memory AI is powering innovative new functionality in the home. Everyday activities such as home security monitoring, unlocking doors, food shopping and baby monitoring become easier and more convenient with AI. Mobile phones and consumer electronics are part of everyday life. The next phase of innovation, powered by AI, is enabling these products to AI enables car and truck drivers quickly get from A to B. Emerging AI applications include driver alertness warnings, driver safety feedback Xnor's award winning technology introduced a novel network architecture designed for the edge. Xnor builds on top of YOLO and other state-of-the-art AI innovations to build custom models of unparalleled efficiency and accuracy, and optimized by being generated > We're pleased to offer Xnor's advanced AI capabilities on > Ambarella's low power, HD camera SoCs. helping to enable a new > generation of intelligent IoT cameras, including smart home > monitoring devices, capable of delivering an*lytics at the edge. AI for Everyone, Everywhere may sound like a science-fiction slogan, but it's actually the name given to software from Xnor.ai that's