Powering next-gen services with AI in regulated industries
Businesses in highly-regulated industries like financial services, insurance, pharmaceuticals, and health care are increasingly turning to AI-powered tools to streamline complex and sensitive tasks. Conversational AI-driven interfaces are helping hospitals to track the location and delivery of a patient’s time-sensitive cancer drugs. Generative AI chatbots are helping insurance customers answer questions and solve problems. And agentic…
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Are we ready to hand AI agents the keys?
On May 6, 2010, at 2:32 p.m. Eastern time, nearly a trillion dollars evaporated from the US stock market within 20 minutes—at the time, the fastest decline in history. Then, almost as suddenly, the market rebounded. After months of investigation, regulators attributed much of the responsibility for this “flash crash” to high-frequency trading algorithms, which…
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Why humanoid robots need their own safety rules
Last year, a humanoid warehouse robot named Digit set to work handling boxes of Spanx. Digit can lift boxes up to 16 kilograms between trolleys and conveyor belts, taking over some of the heavier work for its human colleagues. It works in a restricted, defined area, separated from human workers by physical panels or laser…
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Inside Amsterdam’s high-stakes experiment to create fair welfare AI
This story is a partnership between MIT Technology Review, Lighthouse Reports, and Trouw, and was supported by the Pulitzer Center. Two futures Hans de Zwart, a gym teacher turned digital rights advocate, says that when he saw Amsterdam’s plan to have an algorithm evaluate every welfare applicant in the city for potential fraud, he nearly…
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The Pentagon is gutting the team that tests AI and weapons systems
The Trump administration’s chainsaw approach to federal spending lives on, even as Elon Musk turns on the president. On May 28, Secretary of Defense Pete Hegseth announced he’d be gutting a key office at the Department of Defense responsible for testing and evaluating the safety of weapons and AI systems. As part of a string…
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Manus has kick-started an AI agent boom in China
Last year, China saw a boom in foundation models, the do-everything large language models that underpin the AI revolution. This year, the focus has shifted to AI agents—systems that are less about responding to users’ queries and more about autonomously accomplishing things for them. There are now a host of Chinese startups building these general-purpose…
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What’s next for AI and math
MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. The way DARPA tells it, math is stuck in the past. In April, the US Defense Advanced Research Projects Agency kicked off a new initiative called expMath—short…
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Inside the tedious effort to tally AI’s energy appetite
After working on it for months, my colleague Casey Crownhart and I finally saw our story on AI’s energy and emissions burden go live last week. The initial goal sounded simple: Calculate how much energy is used each time we interact with a chatbot, and then tally that up to understand why everyone from leaders…
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Fueling seamless AI at scale
From large language models (LLMs) to reasoning agents, today’s AI tools bring unprecedented computational demands. Trillion-parameter models, workloads running on-device, and swarms of agents collaborating to complete tasks all require a new paradigm of computing to become truly seamless and ubiquitous. First, technical progress in hardware and silicon design is critical to pushing the boundaries…
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This benchmark used Reddit’s AITA to test how much AI models suck up to us
Back in April, OpenAIannounced it was rolling back an update to its GPT-4o model that made ChatGPT’s responses to user queries too sycophantic. An AI model that acts in an overly agreeable and flattering way is more than just annoying. It could reinforce users’ incorrect beliefs, mislead people, and spread misinformation that can be dangerous—a…
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