Intel® Edge AI – A Program To Train The Developers In Deep Learning And Computer Vision

On April 16, Intel and Udacity jointly announced their new Intel® Edge AI for IoT Developers Nanodegree program to train the developer community in deep learning and computer vision. If you are wondering where AI is headed, now you know, it’s headed to the edge. Edge computing is the concept of storing data and computing data directly at the location where it is needed.

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The IKEA Showroom At Your Home With Help Of Mobile Technology And Deep Learning

The company has taken a user-centric approach to how its customers’ data is used, in line with the IKEA customer data promise based on respect for people and their privacy. Accordingly, any photographs used with the new room design capability can be stored, reduced to just data components, or deleted entirely.

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Leveraging Artificial Intelligence And Machine Learning During A Pandemic

To say that change is a constant is an understatement with the coronavirus turning the whole world upside down. Paired with accelerating cloud technologies where there seems to be no “finish line,” we find ourselves in an environment that is more and more of a challenge for the IT skills of internal teams to keep up.

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Time To Build “Picks And Shovels” For Machine Learning

Many multi-billion-dollar companies have been built by providing tools to make software development easier and more productive. Venture capitalists like to refer to businesses like these as “pick and shovel” opportunities, a reference to Mark Twain’s famous line: “When everyone is looking for gold, it’s a good time to be in the pick and shovel business.”

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Machine Learning: Living In The Age Of AI | A WIRED Film

“Machine Learning: Living in the Age of AI,” examines the extraordinary ways in which people are interacting with AI today. Hobbyists and teenagers are now developing tech powered by machine learning and WIRED shows the impacts of AI on schoolchildren and farmers and senior citizens, as well as looking at the implications that rapidly accelerating technology can have.

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The Power And Limits Of Deep Learning

Deep Learning (DL) has enabled significant progress in computer perception, natural language understanding, and control. Almost all these successes rely on supervised learning, where the machine is required to predict human-provided annotations, or model-free reinforcement learning, where the machine learns policies that maximize rewards. Supervised learning paradigms have been extremely successful for an increasingly large number of practical applications such as medical image analysis, autonomous driving, virtual assistants, information filtering, ranking, search and retrieval, language translation, and many more.

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