The latest from phyBlog

Welcome to the phyBLOG. Here you’ll find the software release announcements, upcoming events, webinar recaps, and other fun stuff!

17
Mar
News

Meet Maddy from Customer Engineering

Engineering was a foreign world which has made learning and exploring this subject even more enthralling.

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11
Mar
News

Meet Sarah from Human Resources

I love sisterhood, camaraderie, and inspiring one another to “just do you” and ignore the outside pressures.

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10
Mar
News

Meet Lacey from Customer Engineering

Work hard, be humble, be willing to do any job, practice problem solving and learn how to be self-motivated.

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09
Mar
News

Meet Jamie from Software

I was part of different robotics clubs in high school and college, including the UW Husky Satellite Lab, where I really liked the combination of technical knowledge and creativity you get to use to solve various problems.

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04
Feb
Training & Webinars

Combining Inference, Real-Time Robotics, Machine Learning, and AI at the Embedded Edge with PHYTEC and TI Sitara™ Platforms

At the beginning of January a few of my colleagues and I attended CES. We were blown away with how prevalent AI, Machine Learning, millimeter wave, and 5G were at the show. Most of us, in the industry, feel entrenched with the importance of these trendy technologies but we were surprised to see them start to turn to a mainstream audience (consumers). We did notice many of the demonstrations and applications were running on power-hungry X86 systems, cloud compute systems, and custom built silicon. In fact, we rode in a self-driving Lyft and the first thing I noticed was the considerably loud fan noise of whatever machine was in the trunk. One can admire the massive compute power of these systems but at the same time also question their efficiency and physical scalability (scaling down, not up). Many silicon vendors, such as Texas Instruments, are trying to address this concern. Moving intelligence to the ‘Embedded Edge’ allows reduced data transferred over networks, reduced power consumption, distributed, and balanced computing.

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21
Mar
Software Releases

phyCORE-i.MX7 Software Release (BSP-Yocto-FSL-iMX7-PD18.2.1)

Software Release Name: BSP-Yocto-FSL-iMX7-PD18.2.1

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21
Feb
Training & Webinars

phyKARL – AWS Machine Learning and PHYTEC

The Machine Learning at the Edge demo built by PHYTEC showcases a practical Object Classification implementation of Amazon Greengrass, Amazon Machine Learning, ApacheMXnet, and ImageNet.

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