// MIT TECH REVIEW — INTELLIGENZA ARTIFICIALE
The Download: AI’s trillion-dollar gamble and OpenAI’s biology data bid
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.
The results are eye-opening. AI companies will need to achieve an extraordinary increase in productivity just to break even by 2030.
Take a closer look at what it will take for the AI buildout to pay off.
AI needs much more information to make important breakthroughs in curing disease. So last year Ruxandra Teslo, a policy analyst, posted an idea for supercharging medical AI systems: use data from failed biotech companies. By bidding at bankruptcy proceedings, she argued, it might be possible to obtain detailed regulatory filings, manufacturing strategies and safety data, creating what she called “biotech’s lost archive.”
The OpenAI Foundation, the nonprofit parent of OpenAI, announced this week that it will fund her idea, paying to create “high-quality scientific datasets.”
As frontier models become more capable, warnings about AI extinction have become widespread in Silicon Valley. But are the threats really as dangerous as they’re presented?
In the latest MIT Technology Review Roundtable, executive editor Niall Firth, senior AI editor Will Douglas Heaven and AI reporter Grace Huckins took a closer look at the arguments behind those warnings. They discussed what AI extinction could actually mean, how seriously we should take the risks and what, if anything, can be done to reduce them.