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Raising The Bar With The Next Generation Of AI For Chip Design


The semiconductor industry is enjoying renewed growth despite chip shortages plaguing everything from cars to kitchen appliances. But while the chips themselves continue to get faster and smarter, the chip design process itself hasn’t changed that much in 20+ years. It typically takes 2-3 years to design a chip with a large engineering team and tens or hundreds of millions of dollars to get a... » read more

Easier And Faster Ways To Train AI


Training an AI model takes an extraordinary amount of effort and data. Leveraging existing training can save time and money, accelerating the release of new products that use the model. But there are a few ways this can be done, most notably through transfer and incremental learning, and each of them has its applications and tradeoffs. Transfer learning and incremental learning both take pre... » read more

Power/Performance Bits: Aug. 10


Flexible electrodes for thin films Researchers from the University of Queensland and ARC Centre of Excellence in Exciton Science (University of Melbourne) developed a material for flexible, recyclable, transparent electrodes that could be used in things like solar panels, touchscreens, and smart windows. Eser Akinoglu of the ARC Centre of Excellence in Exciton Science said, "The performance... » read more

Are Better Machine Training Approaches Ahead?


We live in a time of unparalleled use of machine learning (ML), but it relies on one approach to training the models that are implemented in artificial neural networks (ANNs) — so named because they’re not neuromorphic. But other training approaches, some of which are more biomimetic than others, are being developed. The big question remains whether any of them will become commercially viab... » read more

Finding And Fixing ML’s Flaws


OneSpin CEO Raik Brinkmann sat down with Semiconductor Engineering to discuss how to make machine learning more robust, predictable and consistent, and new ways to identify and fix problems that may crop up as these systems are deployed. What follows are excerpts of that conversation. SE: How do we make sure devices developed with machine learning behave as they're supposed to, and how do we... » read more