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

AI For Circuit Design Quality, Productivity, And Advanced-Node Mapping


The future of circuit design, encompassing analog, RF/5G, and custom electronic circuits, is set to be revolutionized by the integration of generative AI tools. These advanced tools will not only enhance the quality of designs and boost designer productivity but also facilitate the mapping of designs from older semiconductor process nodes to more advanced nodes such as 3nm and below. This blog ... » read more

How Much AI Is Really Needed?


Tensor Core GPUs have created a generative AI model gold rush. Whether it’s helping students with math homework, planning a vacation, or learning to prepare a six-course meal, generative AI is ready with answers. But that's only one aspect of AI, and not every application requires it. AI — now an all-inclusive term, referring to the process of using algorithms to learn, predict, and make... » read more

Unleashing The Power Of Generative AI In Chip, System, And Product Design


The field of chip, system, and product design is a complex landscape, fraught with challenges that designers grapple with daily. The traditional design process, while robust, often falls short in addressing the increasing demands for efficiency, customization, and innovation. This white paper delves into these challenges, exploring the transformative potential of generative artificial int... » read more

Sweeping Changes For Leading-Edge Chip Architectures


Chipmakers are utilizing both evolutionary and revolutionary technologies to achieve orders of magnitude improvements in performance at the same or lower power, signaling a fundamental shift from manufacturing-driven designs to those driven by semiconductor architects. In the past, most chips contained one or two leading-edge technologies, mostly to keep pace with the expected improvements i... » read more

AI PCB Design: How Generative AI Takes Us From Constraints To Possibilities


Generative artificial intelligence (AI) represents the next great step forward in PCB design. This is, of course, what you might expect me to say. 2023 has been a year dominated by the rise of generative AI, with large language models (LLMs) as the unquestionable poster child. It’s easy to see why; LLMs seemingly fulfill the promise of sentience, while in reality, they’re simply very goo... » 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

Using Generative AI To Connect Lab To Fab Test


Executive Insight: Thomas Benjamin, CTO at National Instruments, sat down with Semiconductor Engineering to discuss a new way of looking at test, using data as a starting point and generative AI as a bridge between different capabilities. SE: What are the big changes you're seeing and how is that affecting movement of critical data from the lab to the fab? Benjamin: If you walk into any m... » read more

Using ML For Improved Fab Scheduling


Expanding fab capacity is slow and expensive even under ideal circumstances. It has been still more difficult in recent years, as pandemic-related shortages have strained equipment supply chains. When integrated circuit demand rises faster than expansions can fill the gap, fabs try to find “hidden” capacity through improved operations. They hope that more efficient workflows will allow e... » read more

Generative AI Training With HBM3 Memory


One of the biggest, most talked about application drivers of hardware requirements today is the rise of Large Language Models (LLMs) and the generative AI which they make possible.  The most well-known example of generative AI right now is, of course, ChatGPT. ChatGPT’s large language model for GPT-3 utilizes 175 billion parameters. Fourth generation GPT-4 will reportedly boost the number of... » read more

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