Industrial AI & MACHINE LEARNING
 

Friday 5/29

 
Industry 4.0 applications generate a huge volume of complex data?big data. The increasing number of sensors and, in general, available data sources require the virtual view of machines, systems, and processes to be ever more detailed. This naturally increases the potential for generating added value along the entire value chain.
 
Division of the algorithm pipeline into embedded, edge, and cloud platforms.
 
The latest release of the C/C++test static analysis tool integrates AI and ML capabilities to assist in secure safety-critical applications development.
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The Zynq UltraScale+ MPSoC integrates an ARM Mali-400MP2 GPU engine, H.264/H.265 VCU, and other core signal processing, memory, networking, and transceiver subsystems that further enhance the AI deployment efficiency on the edge.
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UP Xtreme, from AAEON's UP Board division, is being deployed along with technology from partners including Intel, Milestone, and SAIMOS to bring Smart Surveillance to customers with the UP Xtreme Smart Surveillance kit.
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BMW Group has selected the new NVIDIA Isaac robotics platform for use in its automotive factories, utilizing logistics robots built on advanced AI computing and visualization technologies.
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The key to neutralizing the COVID-19 virus is testing, lots of testing. And the AI experts at SensiML are saying that, with enough data in hand, they can tell you whether you have the infection simply by coughing into a microphone. And the test should produce results that are about 90% accurate.



Wow! To be clear, this does not meet the requirements of a clinical tool, but it?s a fantastic start. When I heard about this, I knew I had to hear more, so I dialed up SensiML?s CEO, Chris Rogers, who explained exactly how it works in our Special Edition of the Embedded Executive podcasts.

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Chris Rogers
 

 
 
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