Research & Development news

The Download: AI doomers, whistleblowing agents, and de-aged livers

15-09-2026 14:10 via technologyreview.com

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.
The AI industry has taken a doomer turn. What now?AI chiefs Dario Amodei, Sam Altman, Elon Musk, and Demis Hassabis are suddenly all in agreement: the latest generation of LLMs aren’t safe and everyone needs to figure out what to do about it. It’s easy to be cynical. With trillion-dollar IPOs in their sights, OpenAI and Anthropic n

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AI models need more data about biology, and OpenAI is paying to create it

15-09-2026 14:00 via technologyreview.com

Last year, the clinical trial policy analyst Ruxandra Teslo posted an idea for super-charging medical AI systems: use data from failed biotech companies.By bidding at their bankruptcy proceedings, she proposed, it might be possible to obtain detailed regulatory filings, manufacturing strategies, and safety data—information usually kept hidden as valuable trade secrets. She called these documents “biotech’s lost archive” and said they could be used to help train AIs that w

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What’s at stake in AI’s trillion-dollar gamble

15-09-2026 12:00 via technologyreview.com

When Jessica Wachter, a finance professor at the University of Pennsylvania’s Wharton School, wanted to assess AI’s impact on the economy over the next few years, she faced a long list of business and technical uncertainties. So she started with what she calls 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 useful and widely deployed AI models wil

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What must happen for AI’s trillion-dollar gamble to pay off

15-09-2026 12:00 via technologyreview.com

When Jessica Wachter, a finance professor at the University of Pennsylvania’s Wharton School, wanted to assess AI’s impact on the economy over the next few years, she faced a long list of business and technical uncertainties. So she started with what she calls 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 useful and widely deployed AI models wil

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