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DarwinAI and Intel generate neural network with 16X faster image classification inferencing speed

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Artificial intelligence startup DarwinAI has announced that its Generative Synthesis platform has been used with Intel technology and optimizations to generate neural networks with a 16.3 times improvement in image classification inference performance.

The results of the optimization are shared by Intel in a solution brief. The brief describes how Intel engineers used Intel Optimizations for TensorFlow with Intel Math Kernel Library (Intel MKL and Intel MKL-DNN) to run image classification performance tests with ResNet50 and NASNet. DarwinAI’s platform delivered a 16.3 times improvement in inference speed for ResNet50 over baseline measurements on an Intel Xeon Platinum 8153 processor, and a 9.6 times improvement in inference speed for NASNet.

DarwinAI’s patented “AI building AI” technology dramatically reduces the size, complexity, and guesswork associated with designing efficient, high-performance deep learning systems, according to the announcement. It also facilitates “explainable” deep learning with “root cause analysis” features via AI-powered explainability tools.

“The complexity of deep neural networks makes them a challenge to build, run and use, especially in edge-based scenarios such as autonomous vehicles and mobile devices where power and computational resources are limited,” observes DarwinAI CEO Sheldon Fernandez. “Our Generative Synthesis platform is a key technology in enabling AI at the edge – a fact bolstered and validated by Intel’s solution brief.”

DarwinAI is a member of Intel’s AI Builders Program, and has won recognition including a Frost and Sullivan 2019 Technology Innovation Award, and a place among Hello Tomorrow 2019’s Top 500 Deep Tech Startups.

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