Connected data, AI, and advanced modeling are helping scientists accelerate research and develop more sustainable materials. As companies look to accelerate innovation with artificial intelligence, cloud computing, and advanced modeling, the primary challenge is connecting new technologies to reliable data, scientific expertise, and the practical realities of bringing products to market. For specialty chemicals manufacturer Lubrizol, digital transformation is all about giving researchers the tools to test ideas faster, make better-informed decisions, and develop more sustainable materials without compromising performance. Girish Rao, vice president of information technology at Lubrizol, says the company is building a digital foundation that connects business processes, modern data platforms, and cloud infrastructure to support its research and development (R&D) teams. Their goal is to combine decades of accumulated technical data with the deep expertise of chemists and engineers who understand customer needs as well as the physical constraints of their work. Data scientists can help identify patterns, test new hypotheses, and model possibilities before researchers conduct physical experiments.

Join a subscriber-only conversation exploring possible paths to keep your mind going. In an effort to reach an elusive continuity of the self, some far-thinking technologists are working on ways to keep your brain going--even beyond death. Join science editor Mary Beth Griggs and senior editor for biomedicine Antonio Regalado for a conversation exploring possible paths to keep your mind going, including gradual brain replacement and uploading our memories to the cloud. Technology that lets us "speak" to our dead relatives has arrived. "We were looking at it wrong": The explosive claim that's upended the AI world Will Douglas Heaven 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 An AI "mind-reading" tool can reconstruct what you're looking at from a brain scan Scientists hope it could be used to reconstruct a person's inner thoughts, mental images, or even dreams. New studies pour cold water on a prominent rejuvenation idea.

Data lineage is the new security perimeter, providing the visibility needed for governance, accountability, and trust, without impeding AI adoption at scale. A sales representative asks an AI agent for customer pricing, and the agent pulls data from multiple sources: restricted pricing systems, internal communications, and archived quotes. The output looks accurate to the agent, so a second agent uses the data to draft the proposal for the sales rep. When it's discovered that the proposal includes unapproved, confidential, and sensitive information, no one can trace where the problematic data entered the workflow or how it spread across systems, files, and agents. This scenario illustrates why AI governance needs to evolve, rapidly and dynamically. As more enterprises begin to use agentic AI in daily workflows, they're realizing that they must manage more than static files; they must manage moving and fragmented data that is continuously ingested, copied, summarized, transformed, reused, and redistributed in new forms.

How establishing a company brain can support more accurate, cost-effective AI and autonomous agents. 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 struggle to extract returns on their AI investments. An MIT Technology Review Insights poll finds that while every organization surveyed is using AI today to some degree, fewer than one in five (16%) are extracting transformative value from their deployments.

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.