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Forbes

Forbes reporter Joe McKendrick spotlights a study by researchers from the MIT Center for Collective Intelligence evaluating “the performance of humans alone, AI alone, and combinations of both.” The researchers found that “human–AI systems do not necessarily achieve better results than the best of humans or AI alone,” explains graduate student Michelle Vaccaro and her colleagues. “Challenges such as communication barriers, trust issues, ethical concerns and the need for effective coordination between humans and AI systems can hinder the collaborative process.”

Forbes

Prof. David Autor has been named a Senior Fellow in the Schmidt Sciences AI2050 Fellows program, and Profs. Sara Beery, Gabriele Farina, Marzyeh Ghassemi, and Yoon Kim have been named Early Career AI2050 Fellows, reports Michael T. Nietzel for Forbes. The AI2050 fellowships provide funding and resources, while challenging “researchers to imagine the year 2050, where AI has been extremely beneficial and to conduct research that helps society realize its most beneficial impacts,” explains Nietzel. 

Wired

Using a new technique developed to examine the risks of multimodal large language models used in robots, MIT researchers were able to have a “simulated robot arm do unsafe things like knocking items off a table or throwing them by describing actions in ways that the LLM did not recognize as harmful and reject,” writes Will Knight for Wired. “With LLMs a few wrong words don’t matter as much,” explains Prof. Pulkit Agrawal. “In robotics a few wrong actions can compound and result in task failure more easily.”

Forbes

Researchers from MIT and elsewhere have compared 12 large language models (LLMs) against 925 human forecasters for a three-month forecasting tournament to help predict real-world events, including geopolitical events, reports Tomas Gorny for Forbes. "Our results suggest that LLMs can achieve forecasting accuracy rivaling that of human crowd forecasting tournaments,” the researchers explain.

Forbes

Forbes reporter John M. Bremen spotlights a new study by MIT researchers that “shows the most skilled scientists and innovations benefitted the most from AI – doubling their productivity – while lower-skilled staff did not experience similar gains.” The study “showed that specialized AI tools foster radical innovation at the technical level within a domain-specific scope, but also risk narrowing human roles and diversity of thought,” writes Bremen. 

Forbes

Writing for Forbes, Senior Lecturer Guadalupe Hayes-Mota SB '08, MS '16, MBA '16 shares insight into how entrepreneurs can use AI to build successful startups. AI “can be a strategic advantage when implemented wisely and used as a tool to support, rather than replace, the human touch,” writes Hayes-Mota. 

Forbes

Research from the Data Provenance Initiative, led by MIT researchers, has “found that many web sources used for training AI models have restricted their data, leading to a rapid decline in accessible information,” reports Gary Drenik for Forbes

Forbes

Researchers at MIT have developed a new AI model capable of assessing a patient’s risk of pancreatic cancer, reports Erez Meltzer for Forbes. “The model could potentially expand the group of patients who can benefit from early pancreatic cancer screening from 10% to 35%,” explains Meltzer. “These kinds of predictive capabilities open new avenues for preventive care.” 

TechCrunch

Arago, an AI startup co-founded by alumnus Nicolas Muller, has been named to the Future 40 list by Station F, which selects “the 40 most promising startups,” reports Romain Dillet for TechCrunch. Arago is “working on new AI-focused chips that use optical technology at the chipset level to speed up operations,” explains Dillet.

TechCrunch

Neural Magic, an AI optimization startup co-founded by Prof. Nir Shavit and former Research Scientist Alex Matveev, aims to “process AI workloads on processors and GPUs at speeds equivalent to specialized AI chips,” reports Kyle Wiggers for TechCrunch. “By running models on off-the-shelf processors, which usually have more available memory, the company’s software can realize these performance gains,” explains Wiggers. 

TechCrunch

Michael Truell '21, Sualeh Asif '22, Arvid Lunnemar '22, and Aman Sanger '22 co-founded Anysphere, an AI startup working on developing Cursor, an AI-powered coding assistant, reports Marina Temkin for TechCrunch.

Forbes

Researchers at MIT have developed a “new type of transistor using semiconductor nanowires made up of gallium antimonide and iridium arsenide,” reports Alex Knapp for Forbes. “The transistors were designed to take advantage of a property called quantum tunneling to move electricity through transistors,” explains Knapp. 

New Scientist

Researchers at MIT have developed a new virtual training program for four-legged robots by taking “popular computer simulation software that follows the principles of real-world physics and inserting a generative AI model to produce artificial environments,” reports Jeremy Hsu for New Scientist. “Despite never being able to ‘see’ the real world during training, the robot successfully chased real-world balls and climbed over objects 88 per cent of the time after the AI-enhanced training,” writes Hsu. "When the robot relied solely on training by a human teacher, it only succeeded 15 per cent of the time.”

Financial Times

Research Scientist Nick van der Meulen speaks with Financial Times reporter Bethan Staton about how automation could be used to help employers plug the skills gap. “You can give people insight into how their skills stack up . . . you can say this is the level you need to be for a specific role, and this is how you can get there,” says van der Meulen. “You cannot do that over 80 skills through active testing, it would be too costly.”

Mashable

Graduate student Aruna Sankaranarayanan speaks with Mashable reporter Cecily Mauran the impact of political deepfakes and the importance of AI literacy, noting that the fabrication of important figures who aren’t as well known is one of her biggest concerns. “Fabrication coming from them, distorting certain facts, when you don’t know what they look like or sound like most of the time, that’s really hard to disprove,” says Sankaranarayanan.