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Semiconductor Engineering .:. The Week In Review: Design

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The FTC has given the go-ahead to ON Semiconductor's acquisition of Fairchild Semiconductor. As part of the requirements, ON Semiconductor had to divest its planar insulated gate bipolar transistor business, which will be sold to Littelfuse. The deal has been pending since November 2015 and offers 20 per Fairchild share, approximately 2.4 billion. Sidense demonstrated successful operation of its SHF 1T-OTP one-time programmable memory macros on TSMC's 16FF and 16FFC process nodes. For 16nm implementation, Sidense is adding several enhancements to its architecture including low-voltage reads along with a differential read mode and enhanced security features.


Cadence DSP Targets Neural Network Development EE Times

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SAN FRANCSICO--Neural networks--artificial intelligence processing systems inspired by the human brain--are a hot topic in technology, as large companies like Facebook, Google and Microsoft are developing them and putting them into use. Most neural network technology in place today runs on graphics processing units (GPUs) from Nvidia Corp. and others. EDA and intellectual property vendor Cadence Design Systems Inc. stepped into the fray on on Monday (May 2), rolling out a new version of its Tensilica Vision processing core optimized specifically for vision/deep learning applications. "Everybody is spending a lot of time developing a lot of research and producing a lot of technology," said Pulin Desai, director of product marketing for Cadence's Imaging/Vision Group, in an interview with EE Times. "The market is very hot.


AI in the News – News Stories on AI & ML

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Reactful offers web optimization platform to stimulate visitors' behavior UK's new 112 million science building opens Wednesday Intel blasts back at Nvidia, saying Xeon dominates 97% of A.I. servers How a pair of auto industry giants are fast-tracking'level 5' driverless cars for 2019 Nvidia's new Tegra chip can avoid trouble with the traffic police Machine learning could find an answer to Parkinson's progression This A.I. from Boomerang Predicts What Emails Will Get a Response How do I call Cognitive Services from Azure Machine Learning?


Vision is the next big challenge for chips

ZDNet

In my previous post on the recent Linley Processor Conference, I wrote about the ways that semiconductor companies are developing heterogeneous systems to reach higher levels of performance and efficiency than with traditional hardware. One of the areas where this is most urgently needed is vision processing, a challenge that got a lot of attention at this year's conference.


Scaling up vision and AI performance

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Demand is growing for faster processor architectures to support embedded vision and artificial intelligence. With the demand for image sensors growing rapidly and new opportunities emerging in the mobile, virtual reality (VR), automotive and surveillance markets, demand for applications that are able to mix vision and artificial intelligence (AI) is surging. "We are seeing work on a range of future applications from phones that automatically identify the user, to autonomous cars that are able to recognise an individual's driving style. But whatever the application, all of them are looking at vision sensors that use AI to make decisions," says Pulin Desai, Product Marketing Director for Cadence's Tensilica Vision DSP Product Line. "Each of them brings with them challenges for the design engineer.