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Generative AI improves a wireless vision system that sees through obstructions

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Electronics, Imaging, Machine Learning, Media Lab, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Architecture and Planning, School of Engineering, Sensors, Wireless

MIT researchers have spent more than a decade studying techniques that enable robots to find and manipulate hidden objects by “seeing” through obstacles. Their methods utilize surface-penetrating wireless signals that reflect off concealed items.Now, the researchers are leveraging generative artificial intelligence models to overcome a longstanding bottleneck that limited the precision of prior approaches. The […]

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Can AI help predict which heart-failure patients will worsen within a year?

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Harvard-MIT Health Sciences and Technology, Health care, Health sciences and technology, Jameel Clinic, Machine Learning, Medicine, MIT Schwarzman College of Computing, Research, Research Laboratory of Electronics, School of Engineering

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

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3 Questions: On the future of AI and the mathematical and physical sciences

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Astronomy and astrophysics, Chemistry, Computer science and technology, data, Faculty, IDSS, Interview, Laboratory for Nuclear Science, Machine Learning, Materials science and engineering, Mathematics, MIT Schwarzman College of Computing, National Science Foundation (NSF), Physics, Research, School of Science

Curiosity-driven research has long sparked technological transformations. A century ago, curiosity about atoms led to quantum mechanics, and eventually the transistor at the heart of modern computing. Conversely, the steam engine was a practical breakthrough, but it took fundamental research in thermodynamics to fully harness its power. Today, artificial intelligence and science find themselves at a

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City Union Bank launches AI centre to support banking operations

ai, AI (Artificial Intelligence), AI Business Strategy, AI in Action, Artificial Intelligence, automation, banking, data, Features, Finance, Finance AI

Banks have spent years buying analytics tools and automation software. Now some are taking a different step: building internal spaces where AI can be tested directly on real banking problems. One example emerged in India this month. City Union Bank recently entered a four-party agreement to create a Centre of Excellence for Artificial Intelligence in

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Improving AI models’ ability to explain their predictions

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, data, Electrical engineering and computer science (EECS), Human-computer interaction, Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

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.Concept bottleneck modeling is one method that enables artificial intelligence systems to explain their decision-making process. These methods force a deep-learning model to use a

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New method could increase LLM training efficiency

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Energy, Machine Learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, Research Laboratory of Electronics, School of Engineering

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller steps. These powerful models are particularly good at challenging tasks like advanced programming and multistep planning.But developing reasoning models demands an enormous amount of computation and energy due to inefficiencies in the training process. While

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Study: AI chatbots provide less-accurate information to vulnerable users

ai, AI (Artificial Intelligence), Artificial Intelligence, data, ethics, Machine Learning, Media Lab, MIT Sloan School of Management, Research, School of Architecture and Planning

Large language models (LLMs) have been championed as tools that could democratize access to information worldwide, offering knowledge in a user-friendly interface regardless of a person’s background or location. However, new research from MIT’s Center for Constructive Communication (CCC) suggests these artificial intelligence systems may actually perform worse for the very users who could most

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Exposing biases, moods, personalities, and abstract concepts hidden in large language models

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer science and technology, data, Machine Learning, Mathematics, Research, School of Science, Software

By now, ChatGPT, Claude, and other large language models have accumulated so much human knowledge that they’re far from simple answer-generators; they can also express abstract concepts, such as certain tones, personalities, biases, and moods. However, it’s not obvious exactly how these models represent abstract concepts to begin with from the knowledge they contain.Now a

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3 Questions: Using AI to help Olympic skaters land a quint

ai, AI (Artificial Intelligence), Alumni/ae, Artificial Intelligence, data, IDSS, Interview, Literature, Mechanical engineering, MIT Sloan School of Management, Research, School of Engineering, Sports and fitness

Olympic figure skating looks effortless. Athletes sail across the ice, then soar into the air, spinning like a top, before landing on a single blade just 4-5 millimeters wide. To help figure skaters land quadruple axels, Salchows, Lutzes, and maybe even the elusive quintuple without looking the least bit stressed, Jerry Lu MFin ’24 developed

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Study: Platforms that rank the latest LLMs can be unreliable

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mathematics, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering

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.To narrow down the choice, companies often rely on LLM ranking platforms, which gather user feedback on model interactions to

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