AINewsnow

AI hyperscalers may need to raise productivity 2.7 times by 2030 to justify nearly $1.1 trillion in infrastructure spending through 2027, according to new research.

MIT Technology Review examined research from Jessica Wachter, a Wharton finance professor, and coauthor Jonathan Wachter, who based their estimate on spending by Alphabet, Microsoft, Amazon, Meta and Oracle. Their analysis says the sector would need a 2.7-fold productivity increase by 2030 after ac…

Read the full story at r/artificial ↗

Timeline · 1 report

  1. 2026-09-24 09:07 · r/artificial
    AI hyperscalers may need to raise productivity 2.7 times by 2030 to justify nearly $1.1 trillion in infrastructure spending through 2027, according to new research.

More stories

  1. AI Spending Faces A Trillion-Dollar Reckoning If Productivity Falls Short, MIT Says — r/ArtificialInteligence
  2. GPT-6 Sol and Luna now available on AI Gateway — Vercel Blog
  3. Trump offloads tens of millions in AI, tech shares, led by Microsoft, Amazon, Meta — South China Morning Post Tech
  4. No Shirt, No Shoes, No Service: Amazon Blocks Meta’s Muse AI From Shopping — CNET AI
  5. Meta's standoff with Amazon over Muse could be a sign of things to come — CNBC Technology
  6. Meta’s New AI Agent Is an Instant Hit—and the Backlash Has Already Begun — Wall Street Journal Technology
  7. Retailers are picking sides on AI shopping agents — Semafor Technology
  8. What to Know About Recent A.I. Hacks at Google, Anthropic, OpenAI and Meta — New York Times Technology

Get the daily brief of stories like this at 6:30 every morning →