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Bryan Catanzaro (Nvidia VP): said, "For my team, the cost of compute is far beyond the costs of the employees."
Similarly,
Praveen Neppalli Naga (Uber CTO): said that using AI as coding assistants quickly drained their 2026 AI budget.
This means:
1. It is expensive for Bryan's team, who lead applied deep learning, requiring complex tasks and costing a lot to use AI.
2. Even though entry‑level jobs are at an all‑time low, once you are highly skilled you might get opportunities based purely on technical ability, and you'll have to write code manually so you don't over‑use AI, as Uber's CTO warns.
Side note: an MIT study notes that AI is cost‑competitive in only 23% of job tasks, and in the long run it will become more expensive. So the 77% figure may rise. Get more skilled, use AI surgically for lengthy tasks, and you'll still find a job.
Is that true?
It's just a bubble that will slowly stay with us, but it's not a real threat.
Yeah, no kidding, Sherlock.
Anyone who thinks current AI subscription costs are even close to the actual expense, let alone profit, needs to see a shrink.
I think, in future software engineers will mainly architect system designs and use the most token‑efficient prompts. Also, maybe AI costs more than employee salaries but time is money and AI saves a lot of time, so eventually there will be a balance between AI and humans (if they don't find an infinite energy source).
u/AskGrok, is this true?
That's why some companies prefer actual Indians (AI) over artificial intelligence (AI).
Can anyone explain what "compute cost" includes? Is it mainly pricey GPUs and electricity?