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EETimes - What Enables AI at the Edge?

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While it's clear what's pushing AI to the edge, there are a number of different ways to implement AI at the edge. For engineers, choices are always welcome, but when it comes to AI, it's not always obvious which processors and software are optimal for different applications. The Embedded Vision Summit might be the right place to start for clarity. The event is renowned for being a great place to see real-life demos, as well as for informative sessions on what is both possible and practical today with embedded computer vision and edge AI. Recently this sector has become dominated by AI and machine learning techniques, so as you'd expect, the program reflects that, featuring many AI chip makers and other AI industry experts.


As AI moves to the chip, mobile devices are about to get much smarter

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The branch of artificial intelligence called deep learning has given us new wonders such as self-driving cars and instant language translation on our phones. Now it's about to injects smarts into every other object imaginable. That's because makers of silicon processors from giants such as Intel Corp. and Qualcomm Technologies Inc. as well as a raft of smaller companies are starting to embed deep learning software into their chips, particularly for mobile vision applications. In fairly short order, that's likely to lead to much smarter phones, drones, robots, cameras, wearables and more. "Consumers will be genuinely amazed at the capabilities of these devices," said Cormac Brick, vice president of machine learning for Movidius Ltd., a maker of vision processor chips in San Mateo, Calif.


Embedded World 2018: IoT adds pressure to teach machines to 'see'

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Visual input is arguably the richest source of sensor information. Scientists and engineers have been trying to understand and exploit imaging technologies for many decades now, developing algorithms for vision applications that enable computing machines to'see'.


Embedded World 2018: IoT adds pressure to teach machines to 'see'

#artificialintelligence

Visual input is arguably the richest source of sensor information. Scientists and engineers have been trying to understand and exploit imaging technologies for many decades now, developing algorithms for vision applications that enable computing machines to'see'.


Israeli startup wins $7m investment for retail vision platform

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Israeli computer vision startup, Trigo Vision, has won $7 million in a seed funding round by UK-Israel based Hetz Ventures and Vertex Ventures Israel. Trigo Vision's vision platform is designed for the retail market. It combines a network of ceiling-based cameras with machine vision algorithms to identify customers' shopping items, similar in principle to the Amazon Go store in Seattle, which doesn't have a checkout because it can track what customers put in their shopping basket. The funding will be used to grow the company's core R&D team and build new applications for its technology. 'The founding team has managed to assemble a world-class R&D team to tackle an enormous user experience problem in retail,' commented Yanai Oron, general partner at Vertex Ventures.