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Artificial Intelligence
Tis the season for transformer-centric articles apparently – this is my third within a month. Clearly this is a domain with both great opportunities and challenges: extending large language model (LLM) potential to new edge products and revenue opportunities, with unbounded applications and volumes yet challenges in meeting… Read More
When considering SoC architectures it is easy to become trapped in simple narratives. These assume the center of compute revolves around a central core or core cluster, typically Arm, more recently perhaps a RISC-V option. Throw in an accelerator or two and the rest is detail. But for today’s competitive products that view is a … Read More
Support for AI at the edge has prompted a good deal of innovation in accelerators, initially in CNNs, evolving to DNNs and RNNs (convolutional neural nets, deep neural nets, and recurrent neural nets). Most recently, the transformer technology behind the craze in large language models is proving to have important relevance at… Read More
More than two years ago, Synopsys launched its AI-driven design space optimization (DSO.ai) capability. It is part of the company’s Synopsys.ai EDA suite, an outcome of its overarching AI initiative. Since then, DSO.ai has boosted designer productivity and has been leveraged for 270 production tape-outs. DSO.ai uses machine… Read More
It is tempting to think that everything GPT-related is just chasing the publicity bandwagon and that articles on the topic, especially with evidently impossible claims (as in this case), are simply clickbait. In fact, there are practical reasons for hosting at least a subset of these large language models (LLMs) on edge devices… Read More
Assertion based verification only catches problems for which you have written assertions. Is there a complementary approach to find problems you haven’t considered – the unknown unknowns? Paul Cunningham (Senior VP/GM, Verification at Cadence), Raúl Camposano (Silicon Catalyst, entrepreneur, former Synopsys CTO and now… Read More
Arm just revealed at HotChips their compute subsystems (CSS) direction led by CSS N2. The intent behind CSS is to provide pre-integrated, optimized and validated subsystems to accelerate time to market for infrastructure system builders. Think HPC servers, wireless infrastructure, big edge systems for industry, city, enterprise… Read More
The various algorithms that comprise artificial intelligence (AI) are finding their way into the chip design flow. What is driving a lot of this work is the complexity explosion of new chip designs required to accelerate advanced AI algorithms. It turns out AI is both the problem and the solution in this case. AI can be used to cut … Read More
The automotive industry is undergoing a major transformation. The convergence of electrification, connectivity, driver-assistance technologies, and software-defined vehicles has led to the rise of use of advanced System-on-Chips (SoCs) that drive unprecedented levels of functionality and performance. However, this… Read More
In the rapidly evolving landscape of artificial intelligence (AI), the concept of machine unlearning has emerged as a fascinating and crucial area of research. While the traditional paradigm of AI focuses on training models to learn from data and improve their performance over time, the notion of unlearning takes a step further… Read More
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What if China doesn’t want TSMC’s factories but wants to take them out?