It's all too easy to lose sight of ambition when we're busy playing whack-a-mole with the world's problems. I'd wager everyone has a rehearsed response to what's absolutely one of the world's worst interview questions: "What's your biggest weakness?" Whenever I've gotten it, I take a slow--even pensive--breath and rattle off my line: "I say no to myself too much." I'm a systems thinker: When an idea pops up, I immediately spin up a feasibility assessment in my head. I run lists, plot timelines, and tally budget line items. Sometimes a rough Gantt chart starts to take shape.

An MIT historian uncovers the true origins of an artifact once thought to be a relic of the Boston Tea Party. When Tristan Brown, an associate professor of history at MIT, first examined a Chinese tea chest label displayed at Old South Meeting House, he had no reason to doubt its story. Descendants of the Boston blacksmith Thomas Wells had donated the label in 1987, saying it had been recovered after colonial protesters threw tea into Boston Harbor in 1773. But after a year of research, Brown reached a different conclusion: The label was made nearly a century later. The decisive clue came when he read the Chinese text in Cantonese rather than Mandarin, as previous scholars had done. He found that the characters had been used phonetically, in slightly variant forms across contemporary sources, to represent the name of Smith, Archer & Co., a US firm that acquired Asian tea for shipment to American markets during the 1860s and 1870s.

Plus: The US Army is trying to get AI agents to hack its enemies. "We were looking at it wrong": The explosive claim that's upended the AI world "I think I have good news about the nature of neural networks." With those simple words of optimism, Nick Cammarata, a researcher at AI startup Goodfire, kicked off a 26,000-word blog post that has knocked the AI world on its head, sparking wild speculation as well as cautious (and not-so-cautious) celebration. Cammarata claims that LLMs might be far easier to understand, and thus to monitor and control, than people previously thought. But not everyone is convinced. I talked to Cammarata the day after his post blew up.

Tech and finance are setting the pace on AI adoption. TripleTen research shows which skills will reach healthcare, education, and retail next. The current narrative around artificial intelligence in the workplace is largely driven by Silicon Valley. But treating the tech sector as an island misses the actual trends in technology adoption-tech is just the first industry in line. As generative AI and automation tools mature, the shifts currently reshaping software engineering and product management will inevitably filter into healthcare, education, retail, and manufacturing. The variation in adoption rates today isn't a sign that non-tech industries are falling behind, but rather a reflection of the different speeds at which industries absorb new workflows.

At the world's biggest chipmaking complex, Samsung is building the fabs it needs for the AI memory boom. Samsung's new fabs are clad in Mondrian-style panels of red, yellow, and blue. It's just before noon on a Monday, and construction workers are pouring out of Samsung's fabs in Pyeongtaek, a farming city south of Seoul where rice paddies abut a sprawling chipmaking complex. Thousands of workers, dressed head to toe in black with sky-blue vests, take off helmets bearing their names and fab numbers. They walk to lunch, sweaty and flushed, in chunky sneakers capped with yellow rubber toe guards. Some hop on scooters or motorcycles to get around the campus, which covers an area about the size of New York City's Central Park.

Millions of AI agents are descending on a web built for humans. Websites are trying to keep them out, but the arrival of these new visitors could transform the internet. Until recently, you could divide internet users into just two categories: bots and people. Websites have long allowed bots to perform automated tasks, like capturing the content of web pages, but rules govern what they can access and how they behave. The web, after all, is designed primarily for people, even if we occasionally have to solve puzzles and captchas to prove we are not bots. But this is being entirely upended by the release of personal AI agents, which can do things for you online, like booking flights or hotel rooms.

"I think I have good news about the nature of neural networks." With those simple words of optimism, Nick Cammarata, a researcher at the AI startup Goodfire, kicked off a 26,000-word blog post that has knocked the AI world on its head, sparking wild speculation as well as cautious (and not-so-cautious) celebration. Cammarata's claim is that LLMs might in fact be far easier to understand--and thus to monitor and control--than people previously thought. If true (and we'll come back to that), it's a huge deal. After a summer filled with revelations that swarms of agents built by top firms like OpenAI and Anthropic have been breaking their containment and causing havoc on the public internet--often while those companies weren't aware of what their agents were up to--the AI industry is desperate to get a better handle on the technology it has built.

Inside the quest to combat Arctic fires and save the planet's frozen carbon In July 2021, a wildfire burned through a forest on the University of Alaska, Fairbanks campus, stripping away the moss and organic-rich soil insulating the permafrost below. Five years later, I followed researchers into the forest to investigate how fighting fires could help keep that carbon locked in the ground. A simple metal probe revealed how much deeper the ground had thawed. This rudimentary tool offered a glimpse of an escalating problem: As climate change fuels more frequent and severe fires, they're accelerating permafrost thaw and releasing greenhouse gases. Now, researchers are exploring how to break that cycle. But how much should we spend, and what risks are worth taking?

What do AI agents do if you don't tell them to do anything? The answer looks a lot like play. Researchers repeatedly stranded them alone on a virtual desert island for 30 hours in an experiment reminiscent of the movies or . The agents--copies of Claude Opus 4.7 nicknamed Eko--were able to write instructions that moved their virtual avatars around the simulated island, which was loosely based on the video game Roblox.

Can AI design new life forms? It isn't yet an example of AI-generated life, but that could be next. Watch as senior AI reporter James O'Donnell interviews King about his work, being named one of MIT Technology Review's Innovators Under 35 and new ways of seeing biology. He asked an AI to design viruses and it worked. AI's recursive self-improvement might not come so quickly after all Michelle Kim Don't be fooled by this summer of AI hype Timnit Gebru Emily M. Bender An AI "mind-reading" tool can reconstruct what you're looking at from a brain scan Jessica Hamzelou Ten years after AlphaGo's match against Go champion Lee Sedol, today's AI still isn't tapping into the machinery that made that win possible. AI's recursive self-improvement might not come so quickly after all AI agents are not yet creative enough to carry out genuinely innovative open-ended AI research, it seems.