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  • Hi, I'm David Shaw.

  • And welcome to AI News.

  • In this episode, we'll cover how to gear up

  • to meet the growing needs of AI.

  • We will also introduce you to a few tools that will help

  • you keep up with the AI train.

  • Don't forget to check the links below to learn more.

  • AI now relies on machine learning, a class of algorithms

  • that improve with time.

  • In this article, Intel Fellow Pradeep Dubey and Dr. Amir

  • Khosrowshahi of Nervana take a deeper dive

  • into how machine learning will unlock the true power of AI.

  • They write, "Data doubles every year, growing at a rate faster

  • than compute power.

  • This is the real reason why we are discussing AI,

  • and the reason why machine learning is an effective tool

  • for realizing the power of AI."

  • Did you know that deep neural networks, or DNNs,

  • were used in the 1990s to help with tasks like handwriting

  • recognition on bank checks?

  • Well, today DNNs are used for image recognition, video,

  • and even autonomous driving.

  • But DNNs take a ton of compute resources

  • in the amount of data they process.

  • Intel's Math Kernel Library 2017 introduces the DNN domain,

  • which includes functions necessary to accelerate

  • the most popular image recognition topologies.

  • This includes AlexNet, VGG, GoogleNet, and ResNet.

  • Take a look at this article in the link below to learn more.

  • Don't miss the latest video with [? Meg Naral ?]

  • as she takes us through the deep learning software developer

  • kit.

  • It's a free set of tools for data scientists and software

  • developers for developing, training, and deploying

  • deep learning solutions.

  • The tool now supports Intel Distribution for Caffe.

  • This training tool for image classification

  • includes custom networks for model creation,

  • integration with interactive notebooks,

  • and the ability to install an OS X, or Amazon Web Services.

  • It also supports image classification and image

  • segmentation use cases with interference on floating point

  • 32-bit precision.

  • Thank you for watching, and make sure you like

  • and subscribe to keep getting your AI News each month.

  • And don't forget to check the links below

  • to read up on the information we covered.

Hi, I'm David Shaw.

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