Writing for Wired, Institute Prof. Daron Acemoglu predicts that expectations for generative AI will need to recalibrated during the year ahead. Acemoglu notes that he believes in 2024, “generative AI will have been adopted by many companies, but it will prove to be just ‘so-so automation’ of the type that displaces workers but fails to deliver huge productivity improvements.”
Prof. Jessika Trancik speaks with Associated Press reporter Alexa St. John to discuss electric vehicle emissions and ownership costs. Trancik notes, “buyers should consider total cost of ownership, which for an EV is generally less than that of a gas-powered counterpart due to savings on maintenance and fuel.”
Writing for Wired, research scientist Kate Darling highlights the importance of addressing the fundamentally human behaviors that have been incorporated into AI chatbots. “Research in human-computer and human-robot interaction shows that we love to anthropomorphize—attribute humanlike qualities, behaviors, and emotions to—the nonhuman agents we interact with, especially if they mimic cues we recognize,” writes Darling. “And, thanks to recent advances in conversational AI, our machines are suddenly very skilled at one of those cues: language.”
Prof. David Autor speaks with Bloomberg about the future of generative AI and the technology’s potential impact on productivity and the labor market. “When we interact with AI, we need to learn how to treat it not as authoritative, but as a guide to support decision making, and that’s really critical,” says Autor.
MIT researchers have found that job applicants who used AI to improve spelling and grammar on their resumes were eight percent more likely to be hired, reports Bryan Robinson for Forbes. “If you take two identical workers with the same skills and background, the one with the better-written resume is more likely to get hired,” explains graduate student Emma van Inwegen. “The takeaway is that employers actually care about the writing in the resume; it’s not just a correlation.”
Prof. Canan Dagdeviren and her team have developed a wearable ultrasound patch that can be used to screen for breast cancer at home, reports Grace Browne for Wired. “Dagdeviren wants to give people the opportunity to know what’s happening inside their bodies every day, the same way we check the weather forecast,” writes Browne.
Researchers from MIT have developed, “nanoelectronics they hope can one day enter the brain and treat conditions like Alzheimer’s by monitoring some of these brain patterns,” reports Elizabeth Hlavinka for Salon. “Their device, which they call Cell Rover, serves as a sort of antenna that can help external devices monitor cells.”
Former Postdoc Rana el Kaliouby speaks with Boston Globe reporter Janelle Nanos about her work focused on infusing emotional intelligence into AI. “I’m an optimist, but I’m a realist as well, and I can see where this can go wrong,” says Kaliouby. “I think one of the biggest concerns around AI is bias and how we’re building bias into these models and then deploying them at scale everywhere around the world.”
Dynamic Labs, co-founded by Itai Turbahn '11 and Yoni Goldberg '09, MEng '10, offers “tech for crypto and non-crypto companies alike to create seamless login experiences backed by digital wallets,” reports Marco Quiroz-Gutierrez for Fortune. “The firm’s wallet-based business is twofold,” explains Quiroz-Gutierrez. “It offers a customizable all-in-one service that can either push the crypto wallet technology to the background for less savvy users or put it front and center for Web3 natives.”
Prof. Manolis Kellis speaks with USA Today reporter Josh Peter about the potential impact of AI in developing undetectable performance-enhancing drugs (PEDs). "The most feasible approach would be using generative AI to alter existing PEDs that trigger drug tests in a way that makes those drugs undetectable by current testing technology,” Kellis notes.
During a visit to MIT, National Defense Magazine reporter Sean Carberry met with Prof. John Joannopoulos to learn about how researchers at the Institute for Soldier Nanotechnologies (ISN) “are conducting serious research on nanotechnology that could have a big impact on the battlefield.” Carberry notes that ISN researchers conduct fundamental research and have transitioned “numerous technologies ranging from ‘nanostructure amplifying fluorescent polymers for ultra-sensitive explosive detection’ to photonic crystals that enable thermal photovoltaic power generation in a small device that could replace heavy batteries carried by troops.”
Axios reporter Ina Fried spotlights a new report by Prof. Emeritus Stuart Madnick that finds “2.6 billion personal records have been exposed in data breaches over the past two years and that number continues to grow.” Additionally, Madnick found that” “Data breaches in the US through the first nine months of the year are already 20% higher than for all of 2022.”
Boston Globe reporters Aaron Pressman and Jon Chesto spotlight Liquid AI, a new startup founded by MIT researchers that is developing an AI system that relies on neural-network models that are “much simpler and require significantly less computer power to train and operate” than generative AI systems. “You need a fraction of the cost of developing generative AI, and the carbon footprint is much lower,” explains Liquid AI CEO Ramin Hasani, a research affiliate at CSAIL. “You get the same capabilities with a much smaller representation.”
Prof. Daniela Rus, director of CSAIL, and research affiliates Ramin Hasani, Mathias Lechner, and Alexander Amini have co-founded Liquid AI, a startup building a general-purpose AI system powered by a liquid neural network, reports Kyle Wiggers for TechCrunch. “Accountability and safety of large AI models is of paramount importance,” says Hasani. “Liquid AI offers more capital efficient, reliable, explainable and capable machine learning models for both domain-specific and generative AI applications."
Postdoctoral associate Wen Shuhao and postdoctoral fellows Ma Jian and Lai Lipeng co-founded Xtalpi, a biotech startup that uses “artificial intelligence to find chemical compounds that could be developed into new drugs,” reports Zinnia Lee for Forbes. “By combining AI, quantum physics, cloud computing and robotic automation, Xtalpi said it helps increase the efficiency and success rate of identifying novel drug compounds,” writes Lee. “The company has recently expanded into discovering new chemical compounds for agricultural technology, cosmetics and other applications.”