Engineering a Biomedical Revolution in China

Scientific American | January 02, 2019

For the past 20 years, French neuroscientist Erwan Bezard has spent at least one week every two months in Beijing. Bezard makes the long journey from France to visit the primates bred in Chinese labs. China has become the top destination for research involving these animals, which are invaluable models for studying human disease. Other countries do not breed the primates in such large numbers or to the standard produced in China.
“Some 95% of papers using transgenic monkeys come from China,” says Bezard, director of the Institute of Neurodegenerative Diseases at the University of Bordeaux, and manager of his own lab at the Institute of Laboratory Animal Sciences, Chinese Academy of Medical Sciences. Among recent breakthroughs, researchers at the Chinese Academy of Sciences (CAS) have genetically modified cynomolgus monkeys so they exhibit autistic-like behaviors, to better understand what causes the disorder, and how to treat it.

Spotlight

AMT member Allied Machine and Engineering in Dover, Ohio, cultivates a local skilled workforce by enhancing their education and training initiatives. From Project Lead the Way to interns, Allied is supporting STEM in the local community.

Spotlight

AMT member Allied Machine and Engineering in Dover, Ohio, cultivates a local skilled workforce by enhancing their education and training initiatives. From Project Lead the Way to interns, Allied is supporting STEM in the local community.

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Edge Impulse Raises $15 Million in Series A to Enable a Data-Driven Engineering Revolution with Machine Learning

Edge Impulse, | May 19, 2021

Edge Impulse, the world's leading development platform for machine learning (ML) on edge devices, announced today the completion of a $15 million Series A investment round led by Canaan Partners, with participation from Acrew Capital, Fika Ventures, Momenta Ventures, and Knollwood Investment Advisory. This funding will help the company achieve its goal of democratizing machine learning for millions of developers and engineers working on billions of edge devices. Due to power, bandwidth, and cost constraints, 99% of sensor data is currently unused. Edge Impulse allows this data to be analyzed effectively using edge-optimized machine learning, resulting in smarter products and enhanced privacy. Developers and engineers will use the Edge Impulse framework to build useful datasets, then quickly develop and deploy custom machine learning models to any edge system, from battery-powered sensors to Linux-based GPUs capable of operating actuating pneumatics and robotic arms. With a growing list of silicon partners including Arm, Nordic Semiconductor, NVIDIA, Silicon Labs, STMicroelectronics, Microchip, Arduino, Raspberry Pi, Himax, and Eta Compute, the company's platform is trusted by thousands of developers and businesses looking to utilize sensor data to bring intelligence to the next generation of smart devices. To date, the platform has produced over 23,000 projects and 26 million branded data samples across a variety of verticals, including industrial, infrastructure, wearables, and wildlife conservation, with a global developer group on track to hit 100,000 by 2022. Machine learning allows for a data-driven engineering approach to solving problems that can have an impact in all industries. Using machine learning for data-driven engineering in the Internet of Things will not only create better systems but will also give life to a whole new class of experiences. Surprisingly, thanks to platforms like Edge Impulse, it would become a lot easier to modify, upgrade, and handle. IoT will eventually live up to its original goals and turn consumer products, automotive, agriculture, and engineering from the ground up, thanks to smarter brains and learning capabilities on devices. About Edge Impulse Edge Impulse is the leading embedded machine learning software platform, with over 23,000 ML projects in use around the world. We're on a journey to have the best machine learning development experience on edge devices for sensors, audio, and computer vision at scale. We make highly optimized ML deployable to a wide range of hardware from MCUs to CPUs, from getting started in under five minutes to MLOps in production.

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ENGINEERING TECH

FARO Extends Digital Twin Product Suite with the Acquisition of HoloBuilder, Inc

FARO, HoloBuilder | June 08, 2021

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DESIGN

INTERIOR DESIGN COMPANY HAVENLY ACQUIRES THE INSIDE

HAVENLY | February 19, 2022

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