Thursday 10/17

IAR DevCon
The "machines watching machines" approach prevents unnecessary downtime for unneeded preventative maintenance, as well as for unexpected real-time equipment failures. No humans need to intervene except for equipment maintenance.
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Using AI and machine learning technology, AtomBeam compacts duplicate and extraneous data common in IoT networks.
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Based on Efinix? low-power Quantum architecture, the integration of new MIPI technology makes the Trion programmable devices applicable to use cases ranging from simple bridging or data pre-processing/acceleration to complex video processing and artificial intelligence.
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Qeexo?s AutoML is a one-click, fully automated platform that accelerates the development of machine learning solutions for edge devices.
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Burgeoning trends like autonomous automobiles, the Internet of Things (IoT), and increasingly sophisticated industrial and manufacturing devices, machines and systems are forcing change in the world of embedded systems. The old, purpose-built, closed legacy architectures are giving way to a fluid, software-defined, and connected approach.
This article outlines the differences between machine learning and deep learning, and how to determine when to apply each one.
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