Artificial intelligence

CodeSignal, co-founded by alumnus and CEO Tigran Sloyan, has developed Agentic Skills Intelligence, a new product that “uses AI agents to evaluate the skills people use in their work and links the findings to personalized practice,” writes Forbes’ Ray Ravaglia. CodeSignal has built an AI agent “for each domain in its job taxonomy, such as engineering and sales, along with agents for capabilities that cut across jobs, among them communication and AI literacy,” notes Ravaglia. “The agents draw on systems including Gong, Salesforce, and GitHub, and they score what they find against rubrics the company says are grounded in industrial-organizational psychology.” 

Prof. Sanjay Sarma speaks to Bloomberg’s Saritha Rai about the difficulty of developing dexterous robots for use in the home versus developing factory machines for use in standardized plants. “Heavy work, hazardous tasks have long been the focus of automation,” says Sarma. “Robots seem to be following an evolutionary path–the finer the motor or cognitive skills required, the harder to automate.”  

Writing for Fortune, MIT Innovation Fellow David Siegel SM ’86, PhD ’91, Jeffrey Sonnenfeld and Stephen Henriques examine the timeline of the current investment boom in AI infrastructure. “The market may already have overbuilt relative to the payback window that data center financing assumes. Much of what corporate America spends on AI today funds exploratory pilots,” Siegel, Sonnenfeld and Henriques note. “A pullback to reassess is not only the likely next step, but a healthy one.”  

Prof. Ryan Williams speaks to TechCrunch’s Tim Fernholz about AI platforms refuting the Exponential Time Hypothesis, part of a broader class of problems known as P versus NP. “I do think that it kind of calls into question a lot of the intuitions that we thought we had about … how tractable [hard NP problems] are. I also think that this is probably not the final answer either,” says Williams. AI is “forcing people to be a little more ambitious about the kind of work that they do, and to think more deeply about, okay, if all the things I used to work on are now low-hanging fruit for AI, how can I raise the bar for the kind of scientific questions I want to ask?” 

Prof. Gary Gensler speaks with “Bloomberg Surveillance” hosts Tom Keene and Paul Sweeney about how the current AI investment boom may impact the U.S. economy. “You can be positive about the technology and still say our capital markets tend to overfund in exuberance,” says Gensler. “I think that we will have a deceleration of this AI boom, and then some form of a reversal in the next 18 to 30 months. And the question really, to me, is a little bit about timing: when and then how deep it [the deceleration] is. I think the depth of it is going to be dependent on how much debt is in the system, where it is [and] who holds it.”  

Live on GBH’s “The Curiosity Desk,” hosted by Edgar B. Herwick III, Prof. Adam Berinsky joins Boston Globe reporter Aaron Pressman and Kate Gage from the Cooperative Lab Project for a conversation about the impact of AI on the 2026 midterm elections. Berinsky notes that in the runup to the midterms, voters “need to be careful about what they are paying attention to. I think we want to separate out what is new to AI and what is just communication in general,” says Berinsky. “In elections where margins are tens of thousands of votes in states that can determine the presidency, even really small effects matter.”  

Prof. Eric Klopfer, co-chair of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training, speaks with Newsweek’s Amanda Greenwood and Hollie Silverman about homework in an era of AI. “Students need experience to understand and regulate their AI behaviors,” says Klopfer. “They need to learn how it can augment, rather than replace, their learning, and decide how to use it.”  

Forbes reporter Marshall Shepherd highlights the Probabilistic Bias Correction tool, a new AI system developed by MIT researchers that could extend weather forecasting predictability beyond two weeks.  

The Boston Globe’s Mark Feeney spotlights the “Bounce juggler (W.C. Fields),” a machine modeled after the comedian W.C. Fields, on display at the MIT Museum, that juggles three metal balls and was created by the late Prof. Claude Shannon SM ’40, PhD ’40. “It’s one thing to be known as ‘the father of information theory,’ as Shannon is. His work in mathematics, electrical engineering, cryptography, and computer science was that important,” writes Feeney. “But Shannon was also a chess player, unicyclist, juggler, and inventor. Shannon combined his talent for engineering and imagination with his love of humor and juggling in the ‘Bounce juggler.’”  

In an interview with The Boston Globe’s Rebecca Spiess, Prof. Eric So discusses how AI affects different areas of human cognition, as detailed in his new book “The Collision: What AI Does to Us.” “So many people these days are just really focused on the productivity benefits of AI and what it can do for us. I think what people really should be thinking about is what AI is doing to us in the immediate term,” says So. “AI is changing who we are as thinkers, right now, in our day-to-day lives; in classrooms; in households; in boardrooms across the globe.” 

Prof. Tod Machover’s composition “already and not yet,” was performed by members of the Boston Symphony Orchestra along with an AI system that listens to musicians and adds improvisations, reports A.Z. Madonna for The Boston Globe. “Music is something that’s meant to plumb your soul, and have you discover things,” says Machover. The composition is “about my view of where we are, how to take a deep breath and figure out, gather strength to go somewhere else, and then what a possible future of democracy might be.”  

Prof. Tod Machover speaks to WBUR’s Andrea Shea about “already and not yet” an interactive composition he wrote for the Boston Symphony Orchestra and an AI instrument developed by Machover and graduate student Manaswi Mishra. Machover explains that they designed the AI tools so that they’re “always going to make a kind of variation, a coloration, an extension of what the musician's playing – but exactly what it's going to do I do not have complete control over. I'm trying to show that it [AI] can be integrated in a beautiful, provocative and interesting way in a serious piece of music.”  

Instead of giving AI agents a specific task, MIT researchers put 13 agents, named Eko, alone on a digital desert island for 30 hours, and witnessed the technology playing instead of simply wandering around, writes Fast Company’s Jude Cramer. “The researchers compared Eko’s behavior to common elements of play in animals, including humans,” notes Cramer. “These signs of play include creating their own rules, repeating behaviors with slight variations, setting goals for themselves, and transforming objects and events through make-believe.” 

After observing the behavior of 13 AI agents on a simulated desert island, MIT researchers suggest that allowing agents to explore “without a goal” could be an effective way to teach AI agents new skills, reports Aditya Mehta for TechCrunch. “We normally develop artificial agents by deciding in advance what they should practice, what they should optimize, and what counts as progress,” the researchers write. “Play suggests another regime: give an agent a sufficiently rich and safe world, let it choose what is interesting, and allow useful knowledge to accumulate from the history that follows.” 

Metropolis reporter Anthony Paletta details how MIT’s inaugural Future Fest “brought together visionary leaders across design, technology, and art to address the world’s most pressing problems.” The festival featured the public debut of the redesigned Metropolitan Warehouse, along with conversations, exhibits and demonstrations on architecture, design and technology. “There are no shortage of things going wrong in the world, and others likely to follow,” writes Paletta, “but MIT’s Future Fest offered reassuring proof that we’ve not run out of means to address these problems.”