Semiconductors

Inference 2.0: How enterprise AI is reshaping AI system architectures

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Predictive, generative, and agentic AI are not successive generations. They coexist inside enterprise systems, each placing fundamentally different demands on the underlying compute infrastructure. The enterprise context layer A consumer chatbot relies primarily on pretraining weight memory and optional web search. An enterprise system must operate against information absent from pretraining: engineering specifications, financial ledgers, … Read more

Enterprise AI: Reshaping AI processor architectures

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For the past decade, the artificial intelligence landscape followed a remarkably simple recipe: if you wanted better AI, you built larger models, fed them more data, and added more GPUs. The formula worked, and it worked spectacularly. Every new generation of hardware enabled larger neural networks, and larger neural networks broadened their reach. What began … Read more

GPUs: A high-throughput architecture confronting a workload shift

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There is a growing architectural tension at the heart of modern AI infrastructure. The processors that enabled the deep learning revolution—graphics processing units (GPUs)—remain the dominant engines of large-scale training and inference. Yet the computational profile of frontier language models is evolving in ways that increasingly expose the structural assumptions embedded in GPU design. Memory … Read more