ML-Assisted IC Test Binning With Real-Time Prediction At The Edge


IC Test is a critical part of semiconductor manufacturing and proper die binning and material disposition has an important impact on the overall yield and on the process monitoring and failure mode diagnostics. Edge analytics are becoming an increasingly important aspect of die disposition. By intercepting parts in real-time at the wafer test step, we can save downstream processing needs. In th... » read more

Requirements For The Efficient Implementation Of AI Solutions On Edge Devices


By André Schneider, Olaf Enge-Rosenblatt, and Björn Zeugmann In recent years, there has been a growing tendency to implement data-driven approaches for the continuous monitoring of industrial plants as part of digitalization and Industry 4.0 initiatives. The hope is to detect critical conditions at an early stage, minimize maintenance and downtimes, and continuously achieve high product qu... » read more

AI Races To The Edge


AI is becoming increasingly sophisticated and pervasive at the edge, pushing into new application areas and even taking on some of the algorithm training that has been done almost exclusively in large data centers using massive sets of data. There are several key changes behind this shift. The first involves new chip architectures that are focused on processing, moving, and storing data more... » read more

Maximizing Edge Intelligence Requires More Than Computing


By Toshi Nishida, Avik W. Ghosh, Swaminathan Rajaraman, and Mircea Stan Commercial-off-the-shelf (COTS) components have enabled a commodity market for Wi-Fi-connected appliances, consumer products, infrastructure, manufacturing, vehicles, and wearables. However, the vast majority of connected systems today are deployed at the edge of the network, near the end user or end application, opening... » read more

Unlocking The Power Of Edge Computing With Large Language Models


In recent years, Large Language Models (LLMs) have revolutionized the field of artificial intelligence, transforming how we interact with devices and the possibilities of what machines can achieve. These models have demonstrated remarkable natural language understanding and generation abilities, making them indispensable for various applications. However, LLMs are incredibly resource-intensi... » read more

Software Stack For Edge AI Performance


Developing an agile software stack is important for successful AI deployment on the edge. We regularly encounter new machine learning models created from multiple AI frameworks that leverage the latest primitives and state-of-the-art ML model topologies. This Cambrian explosion has resulted from a fertile open-source community that has embraced AI and is now fueling a wide proliferation of ML m... » read more

Network-on-Chips Enabling Artificial Intelligence/Machine Learning Everywhere


Recently, I attended the AI HW Summit in Santa Clara and Autosens in Brussels. Artificial intelligence and machine learning (AI/ML) were critical themes for both events, albeit from different angles. While AI/ML as a buzzword is very popular these days in all its good and bad ways, in discussions with customers and prospects, it became clear that we need to be precise in defining what type of A... » read more

Generative AI: Transforming Inference At The Edge


The world is witnessing a revolutionary advancement in artificial intelligence with the emergence of generative AI. Generative AI generates text, images, or other media responding to prompts. We are in the early stages of this new technology; still, the depth and accuracy of its results are impressive, and its potential is mind-blowing. Generative AI uses transformers, a class of neural network... » read more

Developing Energy-Efficient AI Accelerators For Intelligent Edge Computing And Data Centers


Artificial intelligence (AI) accelerators are deployed in data centers and at the edge to overcome conventional von Neumann bottlenecks by rapidly processing petabytes of information. Even as Moore’s law slows, AI accelerators continue to efficiently enable key applications that many of us increasingly rely on, from ChatGPT and advanced driver assistance systems (ADAS) to smart edge device... » read more

Semiconductor Industry Is Pulling AI Across A Diversity Of End Uses And Applications


Earlier this month, I had the pleasure of joining a group of industry peers during SEMICON West and the Design Automation Conference in San Francisco for an enlightening panel discussion that we organized titled, “How AI Is Reinventing the Semiconductor Industry Inside and Out.” Moderated by Gartner, I was joined on the panel by senior executives from Advantest, Synopsys and the TinyML Foun... » read more

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