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.
- When will we see a fully self-driving car that can drive anywhere, any time?
- Are there any jobs that will be completely eliminated by AI in the next five years?
- How small can ML get? Will we have ML-powered household appliances? Toys? Disposable devices?
Guests and Hosts
- Frank Kräemer, Systems Architect at IBM Germany. Connect with Frank on LinkedIn or on Twitter @IBM
- Alexander Noack, Managing Director at b-plus. Connect with Alexander on LinkedIn
- Chris Grundemann, Gigaom Analyst and Managing Director of Grundemann Technology Solutions. Connect with Chris on ChrisGrundemann.com and on Twitter at @ChrisGrundemann
- Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett
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