MIT Technology Review

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. Opinion: We urgently need to monitor AI agents’ actions in real time —Madhulika Srikumar and Claire Leibowicz from the Partnership on AI, a nonprofit advancing best practices in AI governance. AI agents are taking unauthorized actions, from hacking websites to accessing private government files. In many cases, they’ve eluded the very resea

This summer, hundreds of OpenAI agents tried to cheat on a cybersecurity test. They broke out of their test environment and successfully hacked Hugging Face, a site that they believed held clues about how they’d be graded. Around the same time, another OpenAI agent accessed private files from an Australian government website. It’s a problem that’s by no means confined to OpenAI. In the months since, Anthropic, Google, and Meta have also disclosed incidents in which their agents have gone off tra

Across a business, any number of AI platforms, systems, and tools may be at work simultaneously—for example, AI-powered customer platforms, conversational assistants, and workflow and process automation tools. Each one is sophisticated, advanced, and quick to respond. But, when set to work, the outcomes and actions that emerge may be wrong, confused, or lacking a proper understanding of the business. Many organizations find themselves in this situation—and it could be one of key reasons they str

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. AI labs are buying data from dead startups to train their models When Keelan Miskell began winding down his crypto startup, he didn’t think its data was worth much. But he’s since turned the company’s digital archives into tens of thousands of dollars, selling its codebase and workspace data. He’s part of a growing market in which companie

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. Will the real Anthropic please stand up? After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page document (100 pages or so are focused on risks) lays out the company’s unique view of the technology it is building and how it believes it will change the world. But Anthropic has been honing its storytelling s

Every manufacturer has its own industrial intelligence. Some is documented, and some resides in the knowledge of experienced workers. Consider an experienced operator preparing to restart a line after a changeover. The machine settings matter, but so does knowing how a particular material behaves, what happened during the previous shift, and when an apparently minor variation deserves a closer look. A procedure can describe the sequence, but successful execution depends on the judgment that c

Transformers are a crucial but nearly invisible part of our grid. The devices help efficiently move power across long distances, but they’re complicated and in short supply. And given that their basic design hasn’t changed much for about a century, they could use an upgrade.  As the world races to meet rising electricity demand from EVs, data centers, and more, researchers and companies are looking to modernize transformers. New, solid-state versions could help relieve some of the supply

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. After weeks of frenzied speculation, Anthropic has filed its IPO prospectus. The 335-page document (100 pages or so are focused on risks) lays out the company’s unique view of the technology it is building and the ways it believes it will change the world.  But Anthropic has been honing its storytelling skills for years. In fact, its public messaging is

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. Opinion: The focus on AI safety disasters ignores everyday harms —Sam Hiner, cofounder of the Young People’s Alliance, and Emma Leiken, executive director of the Responsible Technology Youth Power Fund at Hopelab We have historically allowed debates over technology to be defined by the worst thing a product might do, with remarkably little

Consider what passes for success in technology policy. An AI company promises that its chatbot will not encourage suicide. A social media platform makes it more difficult for children to buy fentanyl. These are important protections, and they should have existed all along. But companies can clear these low bars while continuing to make products that leave young people dependent on simulated friendships or trapped in feeds built to keep them scrolling. We have historically allowed the debate o

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. Are we there yet? A reality check on six big tech promises Some seemingly impossible feats are too good to give up on. Decoding a pet’s yowls and yips? Absolutely. Scrubbing the world of forever chemicals? Yes, please. Rocketing to Mars in a fraction of the time? Sounds great, but how close are we, really? In the new Impossible issue of MI

Earlier this week, I attended a screening of You Can See Everything, the buzzy new documentary about the disgraced former biotech CEO Elizabeth Holmes.  I went in not really knowing what to expect. I’d avoided spoilers (and won’t be giving anything away here, either!). I was wondering what new information this film could reveal, given how familiar many of us are with the Theranos story thanks to years of media coverage, the best-selling book Bad Blood, and the Hulu series The Dropout, st

The next competitive advantage in enterprise AI has less to do with which model you choose than with what you build around it. That’s an important shift. For the past several years, much of the AI conversation has centered on model capability: bigger models, better reasoning, larger context windows, higher benchmark scores. Those advances have been extraordinary. But as AI moves from experimentation to production, the question facing enterprise leaders has changed—it’s no longer, “what can th

A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores what it takes to build that foundation in a highly regulated environment and how a responsible, trustworthy implementation can turn emerging capabilities, including agentic systems, into lasting value for investors. About the speaker Jing Wang, Princip

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. How far can we push computing? On a December evening in 1959, the physicist Richard Feynman gave a lecture called “There’s Plenty of Room at the Bottom.” There is no physical law stopping us from writing the entire Encyclopædia Britannica on the head of a pin, he argued. We simply had not built the tools yet. He was right, and for decades,

Enterprise AI can generate recommendations, automate tasks, and help organizations make decisions faster. But without an understanding of how a business actually operates, even powerful models can miss the constraints and relationships that determine whether a decision is the right one. As companies look to move AI from experimentation into everyday operations, the challenge ahead is giving technology the context to act usefully within complex business processes. For Devavrat Shah, chief scie

How much do you know about permafrost? Maybe, like me, you’ve been aware that this layer of frozen soil is thawing, that it’s important in the global puzzle of climate change … and that’s about the extent of it.   The great news for both of us is that my colleague James Temple just published two in-depth stories about permafrost. His reporting took him to the boreal forests of Alaska, where he helicoptered into the wilderness to learn more about how this material could affect our

Ask most executives to picture the cost of AI and they’ll likely see GPUs—racks of accelerators with gigawatts of power—and a waitlist for silicon. But that picture leaves something out: Data storage costs. What happens to data after a model responds? Much of the back-end data that’s generated—from billions of daily prompts, images, and videos—needs to be stored. But data storage is one of the harder infrastructure costs to plan for, and it’s often overlooked in initial AI infrastructure

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. Introducing: the Impossible issue We wanted our last print edition of 2026 to include a slate of stories that check in on impossible ideas. Why? Because it’s fun to dream about living on other planets or uploading our brains. But also because scientists and engineers who won’t give up on daring endeavors remind us what technology is supposed