Training stays on GPUs; cloud giants move their own inference to in-house chips — resolves 2027-01-31

The debate: whether NVIDIA's GPUs will be replaced by the custom chips cloud giants design for themselves (ASICs: chips built for one job, cheaper and more power-efficient but not general-purpose).

Why it matters: the answer decides where hundreds of billions of dollars of chip purchases go over the next few years, and how much pricing power NVIDIA keeps.

Who is on each side: one camp says custom chips will take the whole market and the other says GPUs cannot be replaced for training; our call is that the two split by job and coexist.

GPUs and ASICs diverge rather than displace each other: training stays on GPUs, while hyperscalers move their own inference to ASICs.

Sources still being linked up — the node(s) behind this call don't have a clickable original link resolved yet. Logged for follow-up.

Reviewed in H1 2027: if GPUs still hold more than 80% of frontier training runs and the ASIC share of hyperscaler inference keeps rising, the call stands.

What would overturn it

Any ASIC winning a major third-party frontier training contract, or the ASIC share of inference flat for two consecutive years.

Jan 31, 2027