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The IoT led to an explosion of data. Though it was once thought the cloud would handle this data, the industry soon realized this was impractical. As a result, edge computing has increased in popularity. One of the most fascinating things about edge computing is that it can be accomplished on a wide range of device categories, from MCUs to complex SoCs with high-end A-class cores, GPUs, and ML accelerators.
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November 15, 10:30 - 11:30 AM CST
- Machine Learning at the Edge
- ML implementation using MCUs with ARM Cortex-M4 and M7
- ML implementation with i.MX application processors
- Vision, Voice and Vibration as ML examples
When and Where
Start Time:Nov 15, 2018 10:30 AM CDT (America/Chicago)
End Time:Nov 15, 2018 11:30 AM CDT (America/Chicago)
Event Visibility & Attendance Policy:Open
- layerscapesupport (Owner)