Forbes reporter Rob Toews spotlights Prof. Daniela Rus, director of CSAIL, and research affiliate Ramin Hasani and their work with liquid neural networks. “The ‘liquid’ in the name refers to the fact that the model’s weights are probabilistic rather than constant, allowing them to vary fluidly depending on the inputs the model is exposed to,” writes Toews.
Prof. Tod Machover speaks with Boston Globe reporter A.Z. Madonna about the restaging of his opera ‘VALIS’ at MIT, which features an AI-assisted musical instrument developed by Nina Masuelli ’23. “In all my career, I’ve never seen anything change as fast as AI is changing right now, period,” said Machover. “So to figure out how to steer it towards something productive and useful is a really important question right now.”
Research fellow Michael Schrage speaks with Fortune reporter Sheryl Estrada about generative AI’s role in the digital economy. “If you truly understand and structure your use cases for generative AI correctly, there’s much less risk associated with the investment,” says Schrage.
Researchers at MIT and elsewhere have developed a medical device that uses AI to evade scar tissue build up, reports Andrew Paul for Popular Science. “The technology’s secret weapon is its conductive, porous membrane capable of detecting when it is becoming blocked by scar tissue,” writes Paul.
Prof. Simon Johnson speaks with Freakonomics guest host Adam Davidson about his new book, economic history, and why new technologies impact people differently. “What do people creating technology, deploying technology— what exactly are they seeking to achieve? If they’re seeking to replace people, then that’s what they’re going to be doing,” says Johnson. “But if they’re seeking to make people individually more productive, more creative, enable them to design and carry out new tasks — let’s push the vision more in that direction. And that’s a naturally more inclusive version of the market economy. And I think we will get better outcomes for more people.”
Researchers at MIT and elsewhere have used artificial intelligence to develop a new antibiotic to combat Acinetobacter baumannii, a challenging bacteria known to become resistant to antibiotics, reports Hannah Kuchler for the Financial Times. “It took just an hour and a half — a long lunch — for the AI to serve up a potential new antibiotic, an offering to a world contending with the rise of so-called superbugs: bacteria, viruses, fungi and parasites that have mutated and no longer respond to the drugs we have available,” writes Kuchler.
Prof. Yoon Kim speaks with Popular Science reporter Charlotte Hu about how large language models like ChatGPT operate. “You can think of [chatbots] as algorithms with little knobs on them,” says Kim. “These knobs basically learn on data that you see out in the wild,” allowing the software to create “probabilities over the entire English vocab.”
Principal Research Scientist Kalyan Veeramachaneni speaks with Fast Company reporter Sam Becker about his work in developing the Synthetic Data Vault, which is helpful for creating synthetic data sets, reports Sam Becker for Fast Company. “Fake data is randomly generated,” says Veeramachaneni. “While synthetic data is trying to create data from a machine learning model that looks very realistic.”
Researchers from MIT and Harvard have explored astrocytes, a group of brain cells, from a computational perspective and developed a mathematical model that shows how they can be used to build a biological transformer, reports Kyle Wiggers for TechCrunch. “The brain is far superior to even the best artificial neural networks that we have developed, but we don’t really know exactly how the brain works,” says research staff member Dmitry Krotov. “There is scientific value in thinking about connections between biological hardware and large-scale artificial intelligence networks. This is neuroscience for AI and AI for neuroscience.
Prof. Mark Tegmark speaks with The Wall Street Journal reporter Emily Bobrow about the importance of companies and governments working together to mitigate the risks of new AI technologies. Tegmark “recommends the creation of something like a Food and Drug Administration for AI, which would force companies to prove their products are safe before releasing them to the public,” writes Bobrow.
Prof. D. Fox Harrell writes for The Guardian about the importance of ensuring AI systems are designed to “reflect the ethically positive culture we truly want.” Harrell emphasizes that: “We need to be aware of, and thoughtfully design, the cultural values that AI is based on. With care, we can build systems based on multiple worldviews – and address key ethical issues in design such as transparency and intelligibility."
Undergraduate student Isabella Struckman and Sofie Kupiec ’23 reached out to the first hundred signatories of the Future of Life Institute’s open letting calling for a pause on AI development to learn more about their motivations and concerns, reports Will Knight for Wired. “The duo’s write-up of their findings reveals a broad array of perspectives among those who put their name to the document,” writes Knight. “Despite the letter’s public reception, relatively few were actually worried about AI posing a looming threat to humanity.”
Prof. Daniela Rus, director of CSAIL, speaks with TechCrunch reporter Brain Heater about liquid neural networks and how this emerging technology could impact robotics. “The reason we started thinking about liquid networks has to do with some of the limitations of today’s AI systems,” says Rus, “which prevent them from being very effective for safety, critical systems and robotics. Most of the robotics applications are safety critical.”
MIT researchers have developed a new tool called “PhotoGuard” that can help protect images from AI manipulation, reports Ross Cristantiello for Boston.com. The tool “is designed to make real images resistant to advanced models that can generate new images, such as DALL-E and Midjourney,” writes Cristantiello.
A working paper co-authored by Prof. John Horton and graduate students Emma van Inwegen and Zanele Munyikwa has found that “AI has the potential to level the playing field for non-native English speakers applying for jobs by helping them better present themselves to English-speaking employers,” reports Medora Lee for USA Today. “Between June 8 and July 14, 2021, [Inwegen] studied 480,948 job seekers, who applied for jobs that require English to be spoken but who mostly lived in nations where English is not the native language,” explains Lee. “Of those who used AI, 7.8% were more likely to be hired.”