tag: machine learning

Manufacturing Bits: April 27
By Mark LaPedus - 27 Apr, 2021 - Comments: 0

Next-gen neuromorphic computing The European Union (EU) has launched a new project to develop next-generation devices for neuromorphic computing systems. The project, called MeM-Scales, plans to develop a novel class of algorithms, devices, and circuits that reproduce multi-timescale processing of biological neural systems. The results will be used to build neuromorphic computing systems th... » read more

Putting Limits On What AI Systems Can Do
By Ed Sperling - 22 Apr, 2021 - Comments: 0

New techniques and approaches are starting to be applied to AI and machine learning to ensure they function within acceptable parameters, only doing what they're supposed to do. Getting AI/ML/DL systems to work has been one of the biggest leaps in technology in recent years, but understanding how to control and optimize them as they adapt isn't nearly as far along. These systems are generall... » read more

Applications, Challenges For Using AI In Fabs
By Mark LaPedus - 14 Apr, 2021 - Comments: 0

Experts at the Table: Semiconductor Engineering sat down to discuss chip scaling, transistors, new architectures, and packaging with Jerry Chen, head of global business development for manufacturing & industrials at Nvidia; David Fried, vice president of computational products at Lam Research; Mark Shirey, vice president of marketing and applications at KLA; and Aki Fujimura, CEO of D2S. Wh... » read more

More Data Drives Focus On IC Energy Efficiency
By Ann Mutschler - 08 Apr, 2021 - Comments: 0

Computing workloads are becoming increasingly interdependent, raising the complexity level for chip architects as they work out exactly where that computing should be done and how to optimize it for shrinking energy margins. At a fundamental level, there is now more data to compute and more urgency in getting results. This situation has forced a rethinking of how much data should be moved, w... » read more

AI In Inspection, Metrology, And Test
By Susan Rambo And Ed Sperling - 06 Apr, 2021 - Comments: 0

AI/ML is creeping into multiple processes within the fab and packaging houses, although not necessarily for the purpose it was originally intended. The chip industry is just beginning to learn where AI makes sense and where it doesn't. In general, AI works best as a tool in the hands of someone with deep domain expertise. AI can do certain things well, particularly when it comes to pattern m... » read more

How Do Machines Learn?
By Weiyang (Will) Zhou - 06 Apr, 2021 - Comments: 0

We depend, or hope to depend, on machines, especially computers, to do many things, from organizing our photos to parking our cars. Machines are becoming less and less "mechanical" and more and more "intelligent." Machine learning has become a familiar phrase to many people in advanced manufacturing. The next natural question people may ask is: How do machines learn? Recognizing diverse obje... » read more

New Uses For AI
By Ed Sperling - 01 Apr, 2021 - Comments: 0

AI is being embedded into an increasing number of technologies that are commonly found inside most chips, and initial results show dramatic improvements in both power and performance. Unlike high-profile AI implementations, such as self-driving cars or natural language processing, much of this work flies well under the radar for most people. It generally takes the path of least disruption, b... » read more

How To Measure ML Model Accuracy
By Bryon Moyer - 01 Apr, 2021 - Comments: 0

Machine learning (ML) is about making predictions about new data based on old data. The quality of any machine-learning algorithm is ultimately determined by the quality of those predictions. However, there is no one universal way to measure that quality across all ML applications, and that has broad implications for the value and usefulness of machine learning. “Every industry, every d... » read more

Xilinx AI Engines And Their Applications
By Xilinx - 31 Mar, 2021 - Comments: 0

This white paper explores the architecture, applications, and benefits of using Xilinx's new AI Engine for compute intensive applications like 5G cellular and machine learning DNN/CNN. 5G requires between five to 10 times higher compute density when compared with prior generations; AI Engines have been optimized for DSP, meeting both the throughput and compute requirements to deliver the hig... » read more

Tradeoffs To Improve Performance, Lower Power
By Ann Mutschler - 11 Mar, 2021 - Comments: 0

Generic chips are no longer acceptable in competitive markets, and the trend is growing as designs become increasingly heterogeneous and targeted to specific workloads and applications. From the edge to the cloud, including everything from vehicles, smartphones, to commercial and industrial machinery, the trend increasingly is on maximizing performance using the least amount of energy. This ... » read more

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