Designing An AI SoC


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


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


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


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


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

Power Issues Rising For New Applications


Managing power in chips is becoming more difficult across a wide range of applications and process nodes, forcing chipmakers and systems companies to rethink their power strategies and address problems much earlier than in the past. While power has long been a major focus in the mobile space, power-related issues now are spreading well beyond phones and laptop computers. There are several re... » read more

Machine Learning For IC Production


Semiconductor Engineering sat down to discuss artificial intelligence (AI), machine learning, and chip and photomask manufacturing technologies with Aki Fujimura, chief executive of D2S; Jerry Chen, business and ecosystem development manager at Nvidia; Noriaki Nakayamada, senior technologist at NuFlare; and Mikael Wahlsten, director and product area manager at Mycronic. What follows are excerpt... » read more

An Integrated Simulation Platform to Validate Autonomous Vehicle Safety


Autonomous driving systems rely upon sensors and embedded software for localization, perception, motion planning and execution. Autonomous driving systems can only be released to the public after developers have demonstrated their ability to achieve extremely high levels of safety. Today’s hands-off autonomous driving systems are largely built with deep learning algorithms that can be trained... » read more

AI In Chip Manufacturing


Ira Leventhal, New Concept Product Initiative vice president at Advantest, talks with Semiconductor Engineering about using analysis and deep learning to make test more efficient and more effective. https://youtu.be/3VVG4JVnjHo » read more

It’s All About The Data


The entire tech industry has changed in several fundamental ways over the past year due to the massive growth in data. Individually, those changes are significant. Taken together, those changes will have a massive impact on the chip industry for the foreseeable future. The obvious shift is the infusion of AI (and its subcategories, machine learning and deep learning) into different markets. ... » read more

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