Just to be clear: this was said by Bryan Catanzaro, the VP of applied deep learning at Nvidia. It is not generalizable to workers using AI tools on their day-to-day work.

A few teams like his are notorious for requiring a ton of computation as they try out different novel approaches, particularly in the context of training rather than inference.

Bryan will sometimes comment on HN, so we may get lucky.

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kingstnap 18 hours ago | parent [-]

It's unclear what he means so it would he good to clarify. Neither the Axios article nor this one provide the details.

> For my team, the cost of compute is far beyond the costs of the employees," Bryan Catanzaro, vice president of applied deep learning at Nvidia, told Axios

He me means they spend more on in house GPUs then employees because of experiments and research thats one thing.

If he means they are running up an OpenAI/Anthropic API bill on coding agents that would be surprising.

	▲	david-gpu 17 hours ago \| parent [-]
		Knowing what his team does, I am quite confident that it is the former. Even years ago Nvidia gave their engineers generous access to some of their own internal GPU farms, so that they could run all sorts of different experiments for software and hardware features. You can look into his team's publications, if you want to learn more about the sort of thing they do.