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Artificial Intelligence
Two recent software-based algorithmic technologies –– autonomous driving (ADAS/AD) and generative AI (GenAI) –– are keeping the semiconductor engineering community up at night.
While ADAS at Level 2 and Level 3 are on track, AD at Levels 4 and 5 are far from reality, causing a drop in venture capital enthusiasm and money. Today,… Read More
As the focal point of the TSMC OIP ecosystem, TSMC has been driving important initiatives over the last few years to bring multi-die systems to the mainstream. As the world is moving quickly toward Generative AI technology and AI-based systems, multi-die and chiplet-based implementations are becoming essential. TSMC recently… Read More
Consensus on smartphone markets hovers somewhere between slight decline and slight growth indicating lack of obvious drivers for more robust growth. As a business opportunity this unappealing state is somewhat offset by sheer volume ($500B in 2023 according to one source) but we’re already close to peak adoption outside of … Read More
When we hear McKinsey & Company, we may think of one of the “Big Three” management consultancies. While that’s true, this firm has a reach and impact that goes far beyond management consulting. According to its website, the firm accelerates sustainable and inclusive growth. While this is an inspirational statement, the… Read More
Over the last few years, transformers have been fundamentally changing the nature of deep learning models, revolutionizing the field of artificial intelligence. Transformers introduce an attention mechanism that allows models to weigh the importance of different elements in an input sequence. Unlike traditional deep learning… Read More
Assertion based verification is a very productive way to catch bugs, however assertions are hard enough to write that assertion-based coverage is not as extensive as it could be. Is there a way to simplify developing assertions to aid in increasing that coverage? Paul Cunningham (Senior VP/GM, Verification at Cadence), Raúl … Read More
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
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Intel’s 14A Is Winning the Race Against Defects