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Taking Machine Learning on the Road with IBM and B-plus | Utilizing AI 2×18

The development of autonomous vehicles is an excellent example of machine learning applied to industrial IoT. In this episode, Alexander Noack of b-plus and Frank Kräemer of IBM Germany join Chris Grundemann and Stephen Foskett to discuss data collection on the road, central processing, and AI model training. Machine learning is part of the development of autonomous vehicle development and is also used in the production of vehicles. It is also used to filter data and enhance processing, and this is the same concept found in many edge and industrial use cases. Edge computing is relevant beyond AI, and these technologies are complementary, with the edge moving right into vehicles, factories, retail outlets, medical facilities, and more.

Three Questions

  1. When will we see a fully self-driving car that can drive anywhere, any time?
  2. Are there any jobs that will be completely eliminated by AI in the next five years?
  3. How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices?

Guests and Hosts

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About the author

Stephen Foskett

Stephen Foskett is an active participant in the world of enterprise information technology, currently focusing on enterprise storage, server virtualization, networking, and cloud computing. He organizes the popular Tech Field Day event series for Gestalt IT and runs Foskett Services. A long-time voice in the storage industry, Stephen has authored numerous articles for industry publications, and is a popular presenter at industry events. He can be found online at TechFieldDay.com, blog.FoskettS.net, and on Twitter at @SFoskett.

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