There’s More To Machine Learning Than CNNs


Neural networks – and convolutional neural networks (CNNs) in particular – have received an abundance of attention over the last few years, but they're not the only useful machine-learning structures. There are numerous other ways for machines to learn how to solve problems, and there is room for alternative machine-learning structures. “Neural networks can do all this really comple... » read more

Leveraging Data In Chipmaking


John Kibarian, president and CEO of PDF Solutions, sat down with Semiconductor Engineering to talk about the impact of data analytics on everything from yield and reliability to the inner structure of organizations, how the cloud and edge will work together, and where the big threats are in the future. SE: When did you recognize that data would be so critical to hardware design and manufact... » read more

Here Come The Economists


Big data is undergoing some big changes. For years, the challenge was getting enough good data to create models for everything from Wall Street trends to traffic routing. But with an influx of data from billions of sensors and electronic transactions, data is no longer in short supply. In fact, there is so much data pouring in that companies need to figure out what to do with it. That requi... » read more

Building AI SoCs


Ron Lowman, strategic marketing manager at Synopsys, looks at where AI is being used and how to develop chips when the algorithms are in a state of almost constant change. That includes what moves to the edge versus the data center, how algorithms are being compressed, and what techniques are being used to speed up these chips and reduce power. https://youtu.be/d32jtdFwpcE    ... » read more

Making AI Run Faster


The semiconductor industry has woken up to the fact that heterogeneous computing is the way forward and that inferencing will require more than a GPU or a CPU. The numbers being bandied about by the 30 or so companies working on this problem are 100X improvements in performance. But how to get there isn't so simple. It requires four major changes, as well as some other architectural shifts. ... » read more

DOM-Based Cross-Site Scripting


DOM-based attacks are a misunderstood, serious, and pervasive source of risk in contemporary web applications. The language that drives the web, JavaScript, is easy to understand and hard to master; junior and senior developers routinely make mistakes. Mix difficulty to master with an enormous attack surface, and you have the perfect storm for widespread vulnerability. These risks expose web ap... » read more

IoT Meets ML


AI and machine learning are the next big things, and they're going make a huge difference in the adoption and capabilities of the IoT. Unlike previous technology approaches, AI, machine learning and deep learning are based on patterns. In effect, they raise up the level of abstraction for data. An image of a cat can be megabytes of data, and a cat taken from all angles may be gigabytes of da... » read more

An Innovator’s Vision


I had the pleasure of talking with [getperson id="11764" comment="Lucio Lanza"], managing director of Lanza techVentures, when I was researching my article on design innovation earlier this month. One thing that sets successful business people apart is their ability to see patterns, to correctly identify how those patterns fit together and progress and, based on those, to know which way to evol... » read more

Building Chips That Can Learn


The idea that devices can learn optimal behavior rather than relying on more generalized hardware and software is driving a resurgence in artificial intelligence, machine leaning, and cognitive computing. But architecting, building and testing these kinds of systems will require broad changes that ultimately could impact the entire semiconductor ecosystem. Many of these changes are wel... » read more

Plugging Holes In Machine Learning


The number of companies using machine learning is accelerating, but so far there are no tools to validate, verify and debug these systems. That presents a problem for the chipmakers and systems companies that increasingly rely on machine learning to optimize their technology because, at least for now, it creates the potential for errors that are extremely difficult to trace and fix. At the s... » read more

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