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

Revolutionizing Product Development And User Experience: The Transformative Power Of Generative AI


Generative AI has become a prominent and versatile solution across various domains, including chip and system development. Its progress and impact have outpaced many other technological advancements, significantly benefiting numerous areas. In the semiconductor industry, EDA tools with generative AI have already established their position by offering unparalleled optimization capabilities. Thes... » read more

Security Becomes Much Bigger Issue For AI/ML Chips, Tools


Security is becoming a bigger issue in AI and machine learning chips, in part because the chip industry is racing just to get new devices working, and in part because it's difficult to secure a new technology that is expected to adapt over time. And unlike in the past, when tools and methodologies were relatively fixed, nearly everything is in motion. Algorithms are being changed, EDA tools ... » read more

AI Adoption Slow For Design Tools


A lot of excitement, and a fair amount of hype, surrounds what artificial intelligence (AI) can do for the EDA industry. But many challenges must be overcome before AI can start designing, verifying, and implementing chips for us. Should AI replace the algorithms in use today, or does it have a different role to play? At the end of the day, AI is a technique that has strengths and weaknesses... » read more

Can AI Write RTL?


Just a few months ago, generative AI was just a promise about what would be possible in the future. Today, nearly everyone with an ounce of curiosity has tried ChatGPT. Most people appear to be somewhat impressed with what it can do, but at the same time see the limitations that it has. As Dean Drako, founder of several companies, told me: "Recently, I needed to write a patent. I described t... » read more

The Next Disruption


Machine learning (ML) is an inherently disruptive technology because the algorithm architectures are evolving so fast and are very compute intensive, requiring innovative silicon for acceptable performance. This blog looks at where we’ve been and where ML is going – into another market ready for disruption. ML started in the data center In the early days of the ML explosion – a mere 8 o... » read more

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