Part 8/12:
A key question raised concerns the hefty capital expenditure (capex) involved in this transition, especially given the massive investments hyperscalers like Amazon, Google, Microsoft, and Meta are making in data centers and GPU infrastructure. Huang responds confidently, framing this spending as an essential, unavoidable evolution driven by physics and economic imperatives.
He explains that Moore's Law—predicting the doubling of transistors on a chip every two years—is slowing down due to physical constraints. This slowdown necessitates alternative strategies, notably accelerated computing facilitated by GPUs. These specialized processors excel in performing parallel computations at scale, making them indispensable for the burgeoning demands of AI and industrial simulation.