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.”
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.
Researchers at MIT have developed a new model for training robots dubbed Heterogeneous Pretrained Transformers (HPT), reports Brain Heater for TechCrunch. The new model “pulls together information from different sensors and different environments,” explains Heater. “A transformer was then used to pull together the data into training models. The larger the transformer, the better the output. Users then input the robot design, configuration, and the job they want done.”
MIT researchers have developed a new training technique called Heterogeneous Pretrained Transformers (HPT) that could help make general-purpose robots more efficient and adaptable, reports Christopher Isak for TechAcute. “The main advantage of this technique is its ability to integrate data from different sources into a unified system,” explains Isak. “This approach is similar to how large language models are trained, showing proficiency across many tasks due to their extensive and varied training data. HPT enables robots to learn from a wide range of experiences and environments.”
Prof. Jacopo Buongiorno speaks with Nature reporter Davide Castelvecchi about how AI has increased energy demand and the future of nuclear energy.
Researchers at MIT have developed “Clio,” a new technique that “enables robots to make intuitive, task-relevant decisions,” reports Jennifer Kite-Powell for Forbes. The team’s new approach allows “a robot to quickly map a scene and identify the items they need to complete a given set of tasks,” writes Kite-Powell.
MIT researchers have developed a security protocol that utilizes quantum properties to ensure the security of data in cloud servers, reports Andrew Corselli for Tech Briefs. “Our protocol uses the quantum properties of light to secure the communication between a client (who owns confidential data) and a server (that holds a confidential deep learning model),” explains postdoc Sri Krishna Vadlamani.
Liquid AI, an MIT startup, is unveiling a new AI model based on a liquid neural network that “has the potential to be more efficient, less power-hungry, and more transparent than the ones that underpin everything from chatbots to image generators to facial recognition systems, reports Will Knight for Wired.
Prof. Daron Acemoglu, a recipient of the 2024 Nobel Prize in economic sciences, speaks with CNBC about the challenges facing the American economy. Acemoglu notes that in his view the coming economic storm is really “both a challenge and an opportunity,” explains Acemoglu. “I talk about AI, I talk about aging, I talk about the remaking of globalization. All of these things are threats because they are big changes, but they’re also opportunities that we could use in order to make ourselves more productive, workers more productive, workers earn more. In fact, even reduce inequality, but the problem is that we’re not prepared for it.”
Graduate student Nouran Soliman speaks with NBC Boston about the use of “personhood credentials,” a new technique that can be used to verify online users as human beings to help combat issues such as fraud and misinformation. “We are trying to also think about ways of implementing a system that incorporates personal credentials in a decentralized way,” explains Soliman. “It's also important not to have the power in one place because that compromises democracy.”
Prof. Evelina Fedorenko speaks with Scientific American reporter Gary Stix about her research demonstrating that “language and thought are, in fact, distinct entities that the brain processes separately.” Speaking about how large language models could be used to help scientists better understand the neuroscience of how language works, Fedorenko explains that "there are many, many questions that we can now ask that had been totally out of reach: for example, questions about [language] development.”
Researchers at MIT and elsewhere have developed “Future You” – an AI platform that uses generative AI to allow users to talk with an AI-generated simulation of a potential future you, reports Sammi Caramela for Vice. The research team hopes “talking to a relatable, virtual version of your future self about your current stressors, future goals, and your beliefs can improve anxiety, quell any obsessive thoughts, and help you make better decisions,” writes Caramela.
Writing for Fast Company, Senior Lecturer Guadalupe Hayes-Mota SB '08, MS '16, MBA '16, explores new approaches to improve the drug development process and more effectively connect scientific discoveries and treatment. “Transforming scientific discoveries into better treatments is a complex challenge, but it is also an opportunity to rethink our approach to healthcare innovation,” writes Hayes-Mota. “Through cross-disciplinary collaboration, leveraging AI, focusing on patient-centered innovation, and rethinking R&D, we can create a future where scientific breakthroughs translate into meaningful, accessible treatments for all.”
Researchers at MIT have found that commercially available AI models, “were more likely to recommend calling police when shown Ring videos captured in minority communities,” reports Kyle Wiggers for TechCrunch. “The study also found that, when analyzing footage from majority-white neighborhoods, the models were less likely to describe scenes using terms like ‘casing the property’ or ‘burglary tools,’” writes Wiggers.
Researchers at MIT have developed GenSQL, a new generative AI system that can be used “to ease answering data science questions,” reports Allison Proffitt for Bio-It World. “Look how much better data science could be if it was easier to use,” says Research Scientist Mathieu Huot. “It’s not perfect yet, but we believe it’s quite an improvement over other options.”