Explosive Growth Ahead


Over the next five years, sales across the semiconductor supply chain will double from $2 trillion to $4 trillion, said Ajit Manocha, president and CEO of SEMI, during the opening presentation at Semicon West this month. These are gigantic numbers, and they reflect some massive shifts now underway across the semiconductor industry. Many chipmakers have been trying to figure out the next big ... » read more

Machine Learning Popularity Grows


Machine learning and deep learning are showing a sharp growth trajectory in many industries. Even the semiconductor industry, which generally has resisted this technology, is starting to changing its tune. Both [getkc id="305" kc_name="machine learning"] (ML) and deep learning (DL) have been successfully used for image recognition in autonomous driving, speech recognition in natural langua... » read more

How Good Is Your Data?


Machines can be taught by other machines. They also can talk to other machines on their own, with no human intervention, which is the great attraction of the Internet of Things. Sensor clusters or other trucks can pass along critical data that alerts a multi-trailered truck to slow down or take a different route. And sensors feeding a variety of data, such as temperature or vibration, can is... » read more

When Digital, Physical Worlds Merge


Semiconductor Engineering sat down with Simon Segars, [getentity id="22186" e_name="ARM's"] CEO, and [getperson id="11764" comment="Lucio Lanza"], managing partner of Lanza techVentures, to talk about changes in the IoT, self-driving vehicles, cloud-based health monitoring, and the impact of machine learning. What follows are excerpts of this conversation. SE: Several years ago the [getkc i... » read more

The Darker Side Of Machine Learning


Machine learning can be used for many purposes, but not all of them are good—or intentional. While much of the work underway is focused on the development of machine learning algorithms, how to train these systems and how to make them run faster and do more, there is a darker side to this technology. Some of that involves groups looking at what else machine learning can be used for. So... » read more

EDA Moves Out Of The Shadows


EDA has long harbored ambitions that are larger than a piece of silicon. The engineering challenges being solved on a nanometric scale are remarkably similar to ones being solved at a much higher level—architectural design, layout, validation, verification, debug, thermal mapping, and a lot more. The problem, at least until recently, is that it has been difficult to gain a foothold in larg... » read more

Machine Learning Meets IC Design


Machine Learning (ML) is one of the hot buzzwords these days, but even though EDA deals with big-data types of issues it has not made much progress incorporating ML techniques into EDA tools. Many EDA problems and solutions are statistical in nature, which would suggest a natural fit. So why is it so slow to adopt machine learning technology, while other technology areas such as vision recog... » read more

A Learning Machine For Machine Learning


Artificial intelligence and machine learning are hot. Many, many startups, exciting new applications and lots of venture money. The technology promises to change the world. Whether it’s autonomous vehicles, domestic robots or machines that replace doctors and lawyers, the implications are astounding, and somewhat frightening. Let’s put the socio-economic dimension of this discussion aside f... » read more

Monday At DAC


The 54th DAC got started today in a very steamy Austin. While we may be a maturing industry, there is certainly no indications that the people within the industry have given up or intend to take it easy. The event really got started late Sunday when Laurie Balch, chief analyst for Gary Smith EDA, delivered her message. She said that the focus is becoming the verticals. "This change in focus is ... » read more

Tech Talk: Neural Networks


Megha Daga, senior technical marketing manager at Cadence, talks with Semiconductor Engineering about convolutional neural networks, including the bandwidth and compute challenges associated with them. » read more

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