tag: deep learning

Factoring Reliability Into Chip Manufacturing
By Ed Sperling - 20 Jun, 2019 - Comments: 0

Making chips that can last two decades is possible, even if it's developed at advanced process nodes and is subject to extreme environmental conditions, such as under the hood of a car or on top of a light pole. But doing that at the same price point as chips that go into consumer electronics, which are designed to last two to four years, is a massively complex challenge. Until a couple of y... » read more

Deep Learning Models With MATLAB And Cortex-A
By Jason Andrews - 13 Jun, 2019 - Comments: 0

Today, I’ve teamed up with Ram Cherukuri of MathWorks to provide an overview of the MathWorks toolchain for machine learning (ML) and the deployment of embedded ML inference on Arm Cortex-A using the Arm Compute Library. MathWorks enables engineers to get started quickly and makes machine learning possible without having to become an expert. If you’re an algorithm engineer interested ... » read more

Week in Review: IoT, Security, Auto
By Jeff Dorsch - 07 Jun, 2019 - Comments: 0

Products/Services Achronix Semiconductor selected the Rambus GDDR6 PHY for its next-generation Speedster7t line of field-programmable gate arrays. The Rambus GDDR6 PHY is used in advanced driver-assistance systems, artificial intelligence, graphics, machine learning, and networking applications. Arm and Marvell Technology Group will work together on design and development of Marvell’s nex... » read more

DAC 2019: Day 3
By Brian Bailey - 06 Jun, 2019 - Comments: 0

Two keynotes get day three of DAC started. The first by John Cohn, Massachusetts Institute of Technology & IBM Watson AI Lab. "I am a nerd. Look back 100 years in processing. We have gone from mechanical computing to where we are today, but it has not been a smooth curve. There are smooth places and then discontinuities. This is when what you were working on no longer works. How we make tho... » read more

System Bits: April 8
By Jeff Dorsch - 08 Apr, 2019 - Comments: 0

Computers trained to design materials Researchers in the University of Missouri’s College of Engineering are applying deep learning technology to educate high-performance computers in the field of materials science, with the goal of having those computers design billions of potential materials. “You can train a computer to do what it would take many years for people to otherwise do,” ... » read more

Designing An AI SoC
By Ed Sperling - 11 Mar, 2019 - Comments: 0

Susheel Tadikonda, vice president of networking and storage at Synopsys, looks at how to achieve economies of scale in AI chips and where the common elements are across all the different architectures. https://youtu.be/fm0kxnj3DuM » read more

Optimizing Deep-Learning Inference For Embedded Devices
By Silexica - 27 Feb, 2019 - Comments: 0

Deep artificial neural networks (ANNs) have emerged as universal feature extractors in various tasks as they approach (and in many cases surpass) human-level performance. They have become fundamental building blocks of almost every modern artificially intelligent (AI) application, from online shop recommendations to self-driving cars. This whitepaper highlights how different challenges relat... » read more

Engineering Talent Shortage Now Top Risk Factor
By Mark LaPedus - 25 Feb, 2019 - Comments: 16

Demand is increasing for engineers and related technical fields in the IC industry, but companies are struggling to find enough talent. The problem is even worse in hot new markets such as AI and 5G, where competition is fierce for experienced workers. The talent shortfall starts with college graduates and professionals in the fields of science, technology, engineering and mathematics (STEM)... » read more

Reliability Becomes The Top Concern In Automotive
By SE Staff - 12 Feb, 2019 - Comments: 4

Reliability is emerging as the top priority across the hottest growth markets for semiconductors, including automotive, industrial and cloud-based computing. But instead of replacing chips every two to four years, some of those devices are expected to survive for up to 20 years, even with higher usage in sometimes extreme environmental conditions. This shift in priorities has broad ramificat... » read more

Power/Performance Bits: Jan. 29
By Jesse Allen - 29 Jan, 2019 - Comments: 0

Neural nets struggle with shape Cognitive psychologists at the University of California Los Angeles investigated how deep convolutional neural networks identify objects and found a big difference between the way these networks and humans perceive objects. In the first of a series of experiments, the researchers showed color images of animals and objects that had been altered to have a diffe... » read more

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