The article discusses the transition from Moore's Law, which has defined computing innovation over the past 50 years, to Huang's Law, named after NVIDIA CEO Jensen Huang. While Moore's Law indicated a doubling of transistor density every 18 to 24 months, Huang's Law describes how GPU performance is now doubling every six months for AI workloads. This shift reflects a more comprehensive acceleration across hardware and software, necessitating infrastructure that caters to exponential scaling demands of modern AI applications. The impact of this new paradigm is palpable, indicating a profound transformation in technology and innovation cycles.
Moore's Law is slowing, and something faster is already replacing it. We're now living in the age of Huang's Law â where AI workloads are accelerating not every two years, but every six months.
Huang's Law describes how GPU performance is doubling every six months... Itâs not just better chips. Itâs better systems: purpose-built GPU architectures and optimized software stacks.
These demands don't scale linearly. They scale exponentially, and they need infrastructure designed to match that curve. That's where Huang's Law comes in.
The impact is already visible across the stack: the LLM and generative AI boom, new cloud primitives, and agent ecosystems that enhance performance and capabilities.
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