Characterized by weakened or damaged heart musculature, heart failure results in the gradual buildup of fluid in a patient’s lungs, legs, feet, and other parts of the body. The condition is chronic and incurable, often leading to arrhythmias or sudden cardiac arrest. For many centuries, bloodletting and leeches were the treatment of choice, famously practiced by barber surgeons in Europe, during a time when physicians rarely operated on patients.
Young adults growing up in the attention economy — preparing for adult life, with social media and chatbots competing for their attention — can easily fall into unhealthy relationships with digital platforms. But what if chatbots weren’t mere distractions from real life? Could they be designed humanely, as moral partners whose digital goal is to be a social guide rather than an addictive escape?
Imagine a world where you could change the designs you see on bags, shirts, and walls whenever you want. Typical clothes would become customizable fashion pieces, while your humble abode could turn into a smart home. That’s the vision of scientists like MIT PhD student Yunyi Zhu ’20, MEng ’21: technology that can “reprogram” the appearance of personal accessories, home decor, and office items.
In high-stakes settings like medical diagnostics, users often want to know what led a computer vision model to make a certain prediction, so they can determine whether to trust its output.
Flying on Mars — or any other world — is an extraordinary challenge. An autonomous spacecraft, operating millions of miles from pilots or engineers who could intervene on Earth, must be able to navigate unfamiliar and changing environments, avoid obstacles, land on uncertain terrain, and make decisions entirely on its own. Every maneuver depends on careful perception, planning, and control systems that are fault-tolerant, allowing the craft to recover if something goes wrong. A single miscalculation can leave a multi-million dollar spacecraft face-down on the surface, ending the mission before it even begins.
Ever had an idea for something that looked cool, but wouldn’t work well in practice? When it comes to designing things like decor and personal accessories, generative artificial intelligence (genAI) models can relate. They can produce creative and elaborate 3D designs, but when you try to fabricate such blueprints into real-world objects, they usually don’t sustain everyday use.
Singapore-MIT Alliance for Research and Technology’s (SMART) Mens, Manus & Machina (M3S) interdisciplinary research group, and National University of Singapore (NUS), alongside collaborators from Massachusetts Institute of Technology (MIT) and Nanyang Technological University (NTU Singapore), have developed an AI control system that enables soft robotic arms to learn a wide repertoire of motions and tasks once, then adjust to new scenarios on the fly without needing retraining or sacrificing functionality. This breakthrough brings soft robotics closer to human-like adaptability for real-world applications, such as in assistive robotics, rehabilitation robots, and wearable or medical soft robots, by making them more intelligent, versatile and safe.
A firm that wants to use a large language model (LLM) to summarize sales reports or triage customer inquiries can choose between hundreds of unique LLMs with dozens of model variations, each with slightly different performance.
MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to test whenever a model is deployed in a new setting.
