The most dangerous policy mistake would be reverting to a 'sliding scale' that allows China to buy chips that are a few generations behind the cutting edge. In the current era of AI, performance is aggregatable. China could simply purchase massive quantities of these slightly older chips to achieve compute power equivalent to frontier systems.
Related Insights
Evaluating export controls by asking if China is still advancing is the wrong metric. The true test is the counterfactual: where would China be *without* the restrictions? The controls act as a significant handicap in a competitive race, not a complete stop, and it's highly likely China would be ahead of the U.S. in AI without them.
Allowing H200 chip sales gives China significant AI compute capability. This short-term revenue boost for NVIDIA won't alter China's long-term policy of reducing reliance on foreign tech, effectively helping a competitor in a strategic race.
The US government's reversal on Nvidia H200 chip sales to China, now with a 25% tax, indicates a strategic shift. The policy is no longer a complete blockade but aims to keep China one generation of chips behind while generating significant tax revenue for the US.
China can compensate for less energy-efficient domestic AI chips by utilizing its vast and rapidly expanding power grid. Since the primary trade-off for lower-end chips is energy efficiency, China's ability to absorb higher energy costs allows it to scale large model training despite semiconductor limitations.
Attempts to undermine Chinese chip maker Huawei by allowing NVIDIA to sell chips to China are flawed. The Chinese government operates outside typical market dynamics and will ensure unlimited demand for Huawei's products, making NVIDIA a temporary gap-filler that inadvertently turbocharges China's AI industry.
Arguments that AI chips are viable for 5-7 years because they still function are misleading. This "sleight of hand" confuses physical durability with economic usefulness. An older chip is effectively worthless if newer models offer exponentially better performance for the price ('dollar per flop'), making it uncompetitive.
Contrary to their intent, U.S. export controls on AI chips have backfired. Instead of crippling China's AI development, the restrictions provided the necessary incentive for China to aggressively invest in and accelerate its own semiconductor industry, potentially eroding the U.S.'s long-term competitive advantage.
China's superior ability to rapidly build energy infrastructure and data centers means it could have outpaced US firms in building massive AI training facilities. Export controls are the primary reason Chinese hyperscalers haven't matched the massive capital spending of their US counterparts.
China is compensating for its deficit in cutting-edge semiconductors by pursuing an asymmetric strategy. It focuses on massive 'superclusters' of less advanced domestic chips and creating hyper-efficient, open-source AI models. This approach prioritizes widespread, low-cost adoption over chasing the absolute peak of performance like the US.
A complete ban on selling chips to China is counterproductive. The ideal policy allows NVIDIA to sell chips that are one or two generations behind state-of-the-art. This strategy keeps Chinese firms dependent on the NVIDIA ecosystem, funds U.S. R&D with sales revenue, and hinders domestic competitors like Huawei from flourishing.
