Using AI to Build Explainable AI with Intel Optimizations and DarwinAI – Intel on AI – Episode 25

Sheldon explains their technology lessens the complexity in designing high performance deep learning solutions and also facilitates explainable deep learning, which makes it possible for an individual to understand why a system gets the decisions it does. Ultimately he explains a recent study conducted by the Intel AI Builders group, in which Darwin-generated networks coupled with Intel Optimizations to get TensorFlow managed to send up to 16.3X operation increase on ResNet50 as well as 9.6X NASNet workloads.

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In this Intel about AI podcast incident : deep neural networks (DNNs), which are arguably the most effective form of AI now, are not simple to construct, run, and also explain. Challenges constitute roadblocks that are substantial . Ironically, AI itself may be utilised to assist data scientists and developers to construct and evaluate DNNs. Sheldon Fernandez, CEO of DarwinAI, joins us to talk about the way DarwinAI is using this’AI building AI’ method within their Generative Synthesis platform.

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