Machine learning

Researchers from MIT and Stanford have found that “artificial intelligence tools like chatbots helped boost worker productivity at one tech company by 14%” reports Jennifer Liu for NBC Boston. “The study is thought to be the first major real-world application of generative AI in the workplace,” writes Liu. “Researchers measured productivity of more than 5,000 customer support agents, based primarily in the Philippines, at a Fortune 500 enterprise software firm over the course of a year.”

Researchers from MIT and elsewhere have found that experienced workers might be more impacted by ChatGPT, reports Mack DeGeurin for Gizmodo. “Customer support agents using a generative AI conversation assistant in a new study saw a 14% uptick in productivity compared to others who didn’t use the tool,” writes DeGeurin.

Popular Science reporter Jamie Dickman writes that using liquid neural networks, MIT researchers have “trained a drone to identify and navigate toward objects in varying environments.” Dickman notes that: “These robust networks enable the drone to adapt in real-time, even after initial training, allowing it to identify a target object despite changes in their environment.”

Researchers at MIT have developed a new type of autonomous drone that uses advanced neural networks to fly, reports Tony Ho Tran for The Daily Beast. “The new design allows the drone to make better decisions when flying through completely new environments,” writes Tran, “and could have future applications in self-driving cars, search and rescue operations, wildlife monitoring, or even diagnosing medical issues.”

Researchers from MIT and elsewhere published a paper exploring the abilities of language models and how they differ from those of humans, reports Will Knight for Wired. Prof. Josh Tenenbaum says “GPT-4 is remarkable but quite different from human intelligence in a number of ways,” writes Knight. “It lacks the kind of motivation that is crucial to the human mind.”

NBC News highlights how researchers from MIT and MGH have developed a new AI tool, called Sybil, that can “accurately predict whether a person will develop lung cancer in the next year 86% to 94% of the time.” NBC News notes that according to experts, the tool "could be a leap forward in the early detection of lung cancer.”

Prof. Marzyeh Ghassemi speaks with WBUR reporter Geoff Brumfiel about her research studying the use of artificial intelligence in healthcare. “When you take state-of-the-art machine learning methods and systems and then evaluate them on different patient groups, they do not perform equally,” says Ghassemi.

Researchers at MIT have created a four-legged robot called DribbleBot, reports Caroline Goggin for WHDH. The robot “can dribble a soccer ball under the same conditions as humans, using onboard sensors to travel across different types of terrain.”

Popular Science reporter Andrew Paul spotlights how researchers from MIT CSAIL have developed a soccer-playing robot, dubbed DribbleBot, that can handle a variety of real-world terrains. “DribbleBot showcases extremely impressive strides in articulation and real-time environmental analysis. Using a combination of onboarding computing and sensing, the team’s four-legged athlete can reportedly handle gravel, grass, sand, snow, and pavement, as well as pick itself up if it falls.”

MIT researchers have created “Dribblebot,” a four-legged robot capable of playing soccer across varying terrain, reports Brian Heater for TechCrunch.

Researchers at MIT have created a four-legged robot capable of dribbling a soccer ball and running across a variety of terrains, reports Ross Cristantiello for Boston.com. “Researchers hope that they will be able to teach the robot how to lift a ball over a step in the future,” writes Cristantiello. “They will also explore how the technology behind DribbleBot can be applied to other robots, allowing machines to quickly transport a range of objects around outside using legs and arms.”

Prof. Marzyeh Ghassemi speaks with Scientific American reporter Sara Reardon about the impact of AI chatbots on medical care. “Ghassemi is particularly concerned that chatbots will perpetuate the racism, sexism and other types of prejudice that persist in medicine—and across the Internet,” writes Reardon. “Scrubbing racism from the Internet is impossible, but Ghassemi says developers may be able to do preemptive audits to see where a chatbot gives biased answers and tell it to stop or to identify common biases that pop up in its conversations with users.”

Principal Research Scientist Leo Anthony Celi co-authored a study that found “a lack of racial and gender diversity could be hindering the efforts of researchers working to improve the fairness of artificial intelligence (AI) tools in health care,” reports Carissa Wong for Nature.

Prof. Carlo Ratti speaks with CNN reporter Sarah Engel about smart cities and the future of AI infrastructure. Ratti says the key to avoiding pitfalls is to keep citizens engaged: “They should be the ones to decide what kind of city they want to live in tomorrow.”

Prof. Aleksander Mądry’s testimony before a House subcommittee was highlighted by Politico fellow Mohar Chatterjee in a recent newsletter exploring how large tech companies are dominating how generative AI technologies are developed and utilized. During his testimony, Mądry emphasized that “very few players will be able to compete, given the highly specialized skills and enormous capital investments the building of such systems requires.”