The Download: AI’s trillion-dollar gamble and OpenAI’s biology data bid
This article examines the massive financial investment in AI data centers and the economic pressure on companies to justify these costs by 2030. It also highlights the OpenAI Foundation's initiative to utilize data from bankrupt biotech firms to advance medical AI research.
Why it matters
The massive capital expenditure in AI infrastructure faces significant economic scrutiny, while new data acquisition strategies could accelerate scientific breakthroughs.
Plus: Nvidia and Meta CEOs have rejected calls for a coordinated AI slowdown.
This is today's edition of The Download , our weekday newsletter that provides a daily dose of what's going on in the world of technology.
When Jessica Wachter, a finance professor at the University of Pennsylvania, wanted to assess AI’s impact on the economy over the next few years, she faced a long list of uncertainties. So she started with a “remarkable fact” that is not in question: a handful of so-called hyperscalers are investing huge amounts of money to build AI data centers.
Instead of trying to predict how widely deployed AI models will be, Wachter asked how fast the hyperscalers’ earnings will need to grow to justify their spending through 2027, when expenditures are expected to reach nearly $1.1 trillion.
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