tag: AI

Regaining U.S. Chip Competitiveness
By Mark LaPedus - 17 Dec, 2020 - Comments: 0

In the IC industry, companies compete in a multitude of different markets. At the same time, there is competition among nations on several different fronts. In technology, for example, various nations are competing for supremacy in 5G, AI and quantum computing. China has rekindled the worldwide competition in semiconductors. Backed by $150 billion in funding, the country is developing its do... » read more

AI And High-NA EUV At 3/2/1nm
By Mark LaPedus - 16 Dec, 2020 - Comments: 1

Semiconductor Engineering sat down to discuss lithography and photomask issues with Bryan Kasprowicz, director of technology and strategy and a distinguished member of the technical staff at Photronics; Harry Levinson, principal at HJL Lithography; Noriaki Nakayamada, senior technologist at NuFlare; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. To vie... » read more

Power Models For Machine Learning
By Brian Bailey - 14 Dec, 2020 - Comments: 1

AI and machine learning are being designed into just about everything, but the chip industry lacks sufficient tools to gauge how much power and energy an algorithm is using when it runs on a particular hardware platform. The missing information is a serious limiter for energy-sensitive devices. As the old maxim goes, you can't optimize what you can't measure. Today, the focus is on functiona... » read more

Fast, Low-Power Inferencing
By Russell Klein - 10 Dec, 2020 - Comments: 1

Power and performance are often thought of as opposing goals, opposite sides of the same coin if you will. A system can be run really fast, but it will burn a lot of power. Ease up on the accelerator and power consumption goes down, but so does performance. Optimizing for both power and performance is challenging. Inferencing algorithms for Convolutional Neural Networks (CNN) are compute int... » read more

Standard Benchmarks For AI Innovation
By Dylan Zika - 10 Dec, 2020 - Comments: 0

There is no standard measurement for machine learning performance today, meaning there is no single answer for how companies build a processor for ML across all use cases while balancing compute and memory constraints. For the longest time, every group would pick a definition and test to suit their own needs. This lack of common understanding of performance hinders customers' buying decis... » read more

Tapping Into Purpose-Built Neural Network Models For Even Bigger Efficiency Gains
By Quenton Hall - 09 Dec, 2020 - Comments: 0

Neural networks can be categorized as a set of algorithms modelled loosely after the human brain that can ‘learn’ by incorporating new data. Indeed, many benefits can be derived from developing purpose-built “computationally efficient” neural network models. However, to ensure your model is effective, there are several key requirements that need to be considered. One critical conside... » read more

The Cyber-Industrial Revolution
By Ed Sperling - 07 Dec, 2020 - Comments: 0

Semiconductors won't save the world, but they certainly will help. In fact, it's arguable whether any significant progress will be made on such issues as global warming or future medical breakthroughs without the aid of ICs. After decades of struggling just to get chips to work at each new process node, the semiconductor industry is moving into a new phase. Processing is now almost ubiquitou... » read more

Transforming Vision Inspection With Machine Learning
By Optimal Plus - 07 Dec, 2020 - Comments: 0

How auto-manufacturers can apply ML & AI algorithms to enhance image analytics on their factory floor and to ensure higher product quality? Discover the next generation visual inspection in our new case study. In this case study , you will learn about: Current limitations of image inspection in the manufacturing industry. The O+ end-to-end solution, which brings machine learning and... » read more

Edge Inference Applications And Market Segmentation
By Geoff Tate - 03 Dec, 2020 - Comments: 0

Until recently, most AI was in data centers/cloud and most of that was training. Things are changing quickly. Projections are AI sales will grow rapidly to tens of billions of dollars by the mid 2020s, with most of the growth in edge AI inference. Data center/cloud vs. edge inference: What’s the difference? The data center/cloud is where inference started on Xeons. To gain efficiency, much ... » read more

Startup Funding: November 2020
By Jesse Allen - 02 Dec, 2020 - Comments: 0

Numerous chipmakers pulled in funding in November 2020, with investors putting money into interconnects, memories, AI hardware, and quantum computing. Launching from stealth was a startup aiming to combine AI and 5G. Autonomous delivery did well, too, with one company raising a massive $500M. This month, we take a look at 28 companies that raised a collective $1.1B. Semi & design Connec... » read more

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