‘The cost of compute is far beyond the costs of the employees’: Nvidia exec says right now AI is more expensive than paying human workers

Reddit r/artificial / 4/29/2026

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Key Points

  • Nvidiaの応用ディープラーニング担当VPブライアン・キャタンザロ氏は、現時点ではAIの計算(コンピュート)コストが人件費を大きく上回っていると述べました。
  • これは、Metaの約8,000人規模の削減やMicrosoftの自発的な買い取りなどの動きが「AIによる人員置き換えの始まり」を示す、という見方に疑問を投げかける内容です。
  • MITの2024年の調査では、視覚が中心となる職務においてAI自動化が経済的に成立するのは23%にとどまり、残り77%では人間がコスト面で有利だとしています。
  • 企業の巨額投資(今年の設備投資は既に7400億ドル、2025年比+69%)が進んでも、AIによる広範な生産性向上や雇用喪失の明確な証拠はまだ見当たらないと報じられています。
  • 短期的にはハードウェア、電力、推論(推論時)コストの高さが効率を下げており、インフラやモデル効率、価格設計の改善によって今後コストバランスが逆転する可能性があると説明されています。
‘The cost of compute is far beyond the costs of the employees’: Nvidia exec says right now AI is more expensive than paying human workers

Nvidia’s vice president of applied deep learning, Bryan Catanzaro, recently stated that for his team, “the cost of compute is far beyond the costs of the employees,” highlighting that AI is currently more expensive than human workers. This challenges the narrative that widespread tech layoffs (including Meta’s planned cut of ~8,000 jobs and Microsoft’s voluntary buyouts) signal an imminent replacement of humans by AI. An MIT study from 2024 supports this, finding that AI automation is economically viable in only 23% of roles where vision is central, and cheaper for humans in the remaining 77%.

Despite heavy AI investment—Big Tech has announced $740 billion in capital expenditures so far this year, a 69% increase from 2025—there is still no clear evidence of broad productivity gains or job displacement from AI. AI spending is driving up costs, with some executives like Uber’s CTO saying their budgets have already been “blown away.” Experts describe the situation as a short-term mismatch: high hardware, energy, and inference costs make AI less efficient than humans right now, though future improvements in infrastructure, model efficiency, and pricing models could tip the balance toward greater economic viability in the coming years.

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