Writing for Forbes, Prof. Daniela Rus, director of CSAIL, makes the case that liquid neural networks “offer an elegant and efficient computational framework for training and inference in machine learning. With their compactness, adaptability, and streamlined computation, these networks have the potential to reshape the landscape of artificial intelligence and drive further breakthroughs in the field.”
Prof. Max Tegmark speaks with Guardian reporter Steve Rose about the potential of artificial intelligence. “The positive, optimistic scenario is that we responsibly develop superintelligence in a way that allows us to control it and benefit from it,” says Tegmark. “If we can build and control superintelligence, we can quickly go from being limited by our own stupidity to being limited by the laws of physics. It could be the greatest empowerment moment in human history.”
Former MIT Prof. Edward Fredkin, “a pioneer in artificial intelligence and a maverick theorist,” has died at 88, reports Alex Williams for The New York Times. Williams notes that Fredkin, who worked on Project MAC during his time at MIT, was “fueled by a seemingly limitless scientific imagination and a blithe indifference to conventional thinking.” Prof. Gerald Sussman recalls that “Ed Fredkin had more ideas per day than most people have in a month.”
MIT Schwarzman College of Computing Dean Daniel Huttenlocher discusses how artificial intelligence has impacted print media at the Aspen Ideas Festival, reports John Frank for Axios. “Most of us grew up in a world where the word print was something that was authoritative,” says Huttenlocher, of how people will need to be on the lookout for misinformation.
MIT Schwarzman College of Computing Dean Daniel Huttenlocher speaks at the Aspen Ideas Festival on how to regulate AI while maximizing its positive impact, reports NBC. “I think when we think about regulation [of artificial intelligence] we need to think about this in the ways we’ve traditionally thought about things – risk, reward, tradeoffs – and that tends to be domain specific,” says Huttenlocher. “It’s hard to have sort of an abstract notion of this new technology and what the risk [and] reward is across all domains.”
Prof. Deb Roy speaks with CNBC reporter Deirdre Bosa about “the relationship between machine-leaning technology and humans.”
Writing for Bloomberg, Prof. Thomas Malone about the need to adapt copyright laws in the era of generative AI. “One promising possibility is to introduce a new body of law based on the premise that different legal protections are appropriate when these massive AI systems can process vast amounts of information far faster and less expensively than humans can,” writs Malone.
Prof. Marzyeh Ghassemi speaks with Yahoo News reporter Rebecca Corey about the benefits and risks posed by the use of AI tools in health care. “I think the problem is when you try to naively replace humans with AI in health care settings, you get really poor results,” says Ghassemi. “You should be looking at it as an augmentation tool, not as a replacement tool.”
Prof. Kevin Esvelt and his students have found that language-generating AI models could make it easier to create pandemic potential pathogens, reports Kelsey Piper for Vox.
MIT researchers and an undergraduate class found that chatbots could be prompted to suggest pandemic pathogens, including specific information not commonly known among experts, reports Ryan Health for Axios. The MIT researchers recommend "pre-release evaluations of LLMs by third parties, curating training datasets to remove harmful concepts, and verifiably screening all DNA generated by synthesis providers or used by contract research organizations."
Writing for The Conversation, postdoc Ziv Epstein SM ’19, PhD ’23, graduate student Robert Mahari and Jessica Fjeld of Harvard Law School explore how the use of generative AI will impact creative work. “The ways in which existing laws are interpreted or reformed – and whether generative AI is appropriately treated as the tool it is – will have real consequences for the future of creative expression,” the authors note.
Researchers at MIT have developed a new artificial intelligence system aimed at helping autopilot avoid obstacles while maintaining a desirable flight path, reports Kyle Wiggers for TechCrunch. “Any old algorithm can propose wild changes to direction in order to not crash, but doing so while maintaining stability and not pulping anything inside is harder,” writes Wiggers.
A study by MIT researchers shows that “workers have cost employers a 25% tax rate, while the rate of software and equipment has stood around 5%,” write Diego Areas Munhoz and Samantha Handler for Bloomberg. “This lopsidedness in tax code gives employers more reason to invest in automating goods like machines and computer software instead of workers.”
Science reporter Robert F. Service spotlights how Prof. Kevin Esvelt is sounding the alarm that “AI could help somebody with no science background and evil intentions design and order a virus capable of unleashing a pandemic.”
“Power and Progress,” a new book by Institute Prof. Daron Acemoglu and Prof. Simon Johnson, has been named one of the best new books on economics by the Financial Times. “The authors’ nuanced take on technological development provides insights on how we can ensure the coming AI revolution leads to widespread benefits for the many, not just the tech bros,” writes Tej Parikh.