Human-computer interaction

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Personalization features can make LLMs more agreeable

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), ethics, Human-computer interaction, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

Many of the latest large language models (LLMs) are designed to remember details from past conversations or store user profiles, enabling these models to personalize responses.But researchers from MIT and Penn State University found that, over long conversations, such personalization features often increase the likelihood an LLM will become overly agreeable or begin mirroring the […]

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Helping AI agents search to get the best results out of large language models

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

Whether you’re a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you’ll find that artificial intelligence tools are becoming the assistants you didn’t know you needed. In particular, many professionals are tapping into the talents of semi-autonomous software systems called AI agents, which can call on AI

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Counter intelligence

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How can artificial intelligence step out of a screen and become something we can physically touch and interact with?That question formed the foundation of class 4.043/4.044 (Interaction Intelligence), an MIT course focused on designing a new category of AI-driven interactive objects. Known as large language objects (LLOs), these physical interfaces extend large language models into

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MIT scientists investigate memorization risk in the age of clinical AI

ai, AI (Artificial Intelligence), Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, cybersecurity, Electrical engineering and computer science (EECS), ethics, Health care, Health sciences and technology, Human-computer interaction, Institute for Medical Engineering and Science (IMES), Jameel Clinic, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Privacy, Public health, Research, School of Engineering, Technology and society

What is patient privacy for? The Hippocratic Oath, thought to be one of the earliest and most widely known medical ethics texts in the world, reads: “Whatever I see or hear in the lives of my patients, whether in connection with my professional practice or not, which ought not to be spoken of outside, I

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MIT researchers “speak objects into existence” using AI and robotics

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Generative AI and robotics are moving us ever closer to the day when we can ask for an object and have it created within a few minutes. In fact, MIT researchers have developed a speech-to-reality system, an AI-driven workflow that allows them to provide input to a robotic arm and “speak objects into existence,” creating

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Researchers discover a shortcoming that makes LLMs less reliable

Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Human-computer interaction, Institute for Medical Engineering and Science (IMES), Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, Technology and society

Large language models (LLMs) sometimes learn the wrong lessons, according to an MIT study.Rather than answering a query based on domain knowledge, an LLM could respond by leveraging grammatical patterns it learned during training. This can cause a model to fail unexpectedly when deployed on new tasks.The researchers found that models can mistakenly link certain

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MIT researchers propose a new model for legible, modular software

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

Coding with large language models (LLMs) holds huge promise, but it also exposes some long-standing flaws in software: code that’s messy, hard to change safely, and often opaque about what’s really happening under the hood. Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) are charting a more “modular” path ahead. Their new approach breaks

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New software designs eco-friendly clothing that can reassemble into new items

Artificial Intelligence, Cleaner industry, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Design, Electrical engineering and computer science (EECS), Human-computer interaction, Invention, Machine Learning, Media Lab, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, Research, School of Engineering, Sustainability

It’s hard to keep up with the ever-changing trends of the fashion world. What’s “in” one minute is often out of style the next season, potentially causing you to re-evaluate your wardrobe.Staying current with the latest fashion styles can be wasteful and expensive, though. Roughly 92 million tons of textile waste are produced annually, including the

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Lincoln Lab unveils the most powerful AI supercomputer at any US university

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The new TX-Generative AI Next (TX-GAIN) computing system at the Lincoln Laboratory Supercomputing Center  (LLSC) is the most powerful AI supercomputer at any U.S. university. With its recent ranking from  TOP500, which biannually publishes a list of the top supercomputers in various categories, TX-GAIN joins the ranks of other powerful systems at the LLSC, all supporting

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