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MIT News - Artificial intelligence - Software
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Hybrid AI model crafts smooth, high-quality videos in seconds | MIT News | Massachusetts Institute of Technology
The CausVid tool uses a full-sequence diffusion model to teach an autoregressive system to swiftly create videos. Users can generate clips and modify them on the fly with new prompts, turn a photo into moving scenes, and extend videos.
Q&A: A roadmap for revolutionizing health care through data-driven innovation | MIT News | Massachusetts Institute of Technology
"The Analytics Edge in Healthcare," co-written by MIT Vice Provost for Open Learning Dimitris Bertsimas and two MIT alumni, explores how analytics is driving decisions and outcomes in health care.
Novel AI model inspired by neural dynamics from the brain | MIT News | Massachusetts Institute of Technology
MIT CSAIL researchers developed “linear oscillatory state-space models” to leverage harmonic oscillators. Capturing the stability and efficiency of biological neural systems and translating these principles into a machine learning framework, the LinOSS approach can help predict complex systems.
Making AI models more trustworthy for high-stakes settings | MIT News | Massachusetts Institute of Technology
MIT researchers made a technique that improves the trustworthiness of machine-learning models, which could help improve the accuracy and reliability of AI predictions for high-stakes settings such health care.
Merging design and computer science in creative ways | MIT News | Massachusetts Institute of Technology
MIT graduate student and MAD Fellow Alexander Htet Kyaw combines AI, AR, robotics, and gesture recognition to develop tools like Curator AI, Estimate, and BendShelters — advancing sustainable design, human-computer interaction, and refugee housing through computational and digital fabrication.
Designing a new way to optimize complex coordinated systems | MIT News | Massachusetts Institute of Technology
MIT LIDS researchers have developed a new way of approaching complex problems such as coordinating complicated interactive systems, using simple diagrams as a tool to reveal better approaches to software optimization in deep learning models.
New model predicts a chemical reaction’s point of no return | MIT News | Massachusetts Institute of Technology
MIT researchers developed a machine-learning model that can predict the structures of transition states of chemical reactions in less than a second, with high accuracy. Their model could make it easier for chemists to design reactions that could generate a variety of useful compounds, such as pharmaceuticals or fuels.
“Periodic table of machine learning” could fuel AI discovery | MIT News | Massachusetts Institute of Technology
After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, MIT researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones.
Norma Kamali is transforming the future of fashion with AI | MIT News | Massachusetts Institute of Technology
Fashion designer Norma Kamali leverages generative AI to innovate her designs and redefine creativity. MIT Professional Education's course empowered her to merge art, technology, and sustainability in the fashion industry.
3D modeling you can feel | MIT News | Massachusetts Institute of Technology
MIT CSAIL’s “TactStyle” system uses image prompts to replicate both the visual appearance and touch-based properties of 3D models. It could help create home décor, personal accessories, and tactile learning tools from a single image input.
MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale | MIT News | Massachusetts Institute of Technology
A quarter century after its founding, the McGovern Institute at MIT reflects on its discoveries in the areas of basic neuroscience, neurotechnology, artificial intelligence, brain-body connections, and therapeutics.
Making AI-generated code more accurate in any language | MIT News | Massachusetts Institute of Technology
Researchers developed a more efficient way to control the outputs of a large language model, guiding it to generate text that adheres to a certain structure, like a programming language, and remains error free.
A faster way to solve complex planning problems | MIT News | Massachusetts Institute of Technology
MIT researchers developed a machine-learning-guided technique to solve complex, long-horizon planning problems more efficiently than some traditional approaches, while arriving at an optimal solution that better meets a user’s goals.
New method efficiently safeguards sensitive AI training data | MIT News | Massachusetts Institute of Technology
MIT CSAIL researchers devised a way to maintain an AI model’s accuracy while ensuring attackers can’t extract sensitive information used to train it. The approach is computationally efficient, reducing a longstanding tradeoff between accuracy and privacy.
Could LLMs help design our next medicines and materials? | MIT News | Massachusetts Institute of Technology
A new multimodal tool combines a large language model with powerful graph-based AI models to efficiently find new, synthesizable molecules with desired properties, based on a user’s queries in plain language.
New method assesses and improves the reliability of radiologists’ diagnostic reports | MIT News | Massachusetts Institute of Technology
A new method assesses and improves the reliability of radiologists’ diagnostic reports. The framework helps clinicians choose terms that more accurately reflect the likelihood that certain conditions are present in X-rays.
Vana is letting users own a piece of the AI models trained on their data | MIT News | Massachusetts Institute of Technology
The decentralized platform Vana, which started as an MIT class project, is on a mission to give power back to users. The firm created a user-owned network that allows individuals to upload their data and govern how they are used to train AI models.
Researchers teach LLMs to solve complex planning challenges | MIT News | Massachusetts Institute of Technology
A new large language model framework teaches LLMs to use an optimization solving algorithm to resolve complex, multistep planning tasks. With the LLMFP framework, someone can input a natural language description of their problem and receive a plan to reach their desired goal.
For this computer scientist, MIT Open Learning was the start of a life-changing journey | MIT News | Massachusetts Institute of Technology
MIT Research Scientist Ana Trišović went from a student downloading MIT Open Learning resources in Serbia to becoming a computer scientist at CERN, Harvard, and MIT.
AI tool generates high-quality images faster than state-of-the-art approaches | MIT News | Massachusetts Institute of Technology
A hybrid AI approach known as hybrid autoregressive transformer can generate realistic images with the same or better quality than state-of-the-art diffusion models, but that runs about nine times faster and uses fewer computational resources. The new tool uses an autoregressive model to quickly capture the big picture and then a small diffusion model to refine the details of the image.
Robotic helper making mistakes? Just nudge it in the right direction | MIT News | Massachusetts Institute of Technology
MIT researchers developed a framework that lets a user correct a robot’s behavior during deployment using simple interactions, such as by pointing to an item, tracing a trajectory, or nudging the robot’s arm.
Markus Buehler receives 2025 Washington Award | MIT News | Massachusetts Institute of Technology
MIT Professor Markus Buehler received 2025 Washington Award for groundbreaking accomplishments in computational modeling and mechanics of biological materials, and his contributions to engineering education and leadership in academia.
Collaborating to advance research and innovation on essential chips for AI | MIT News | Massachusetts Institute of Technology
MIT Microsystems Technology Laboratories and GlobalFoundries announce a new research agreement to advance research and innovation on essential chips for AI, particularly in power consumption by data centers and edge devices.
An ancient RNA-guided system could simplify delivery of gene editing therapies | MIT News | Massachusetts Institute of Technology
MIT scientists have uncovered ancient systems with potential to expand the genome editing toolbox. These tandem interspaced guide RNA (TIGR) systems use RNA to guide them to specific sites on DNA.
Streamlining data collection for improved salmon population management | MIT News | Massachusetts Institute of Technology
MIT Professor Sara Beery and PhD student Justin Kay are developing an automated data collection system for monitoring salmon populations in the Pacific Northwest of the United States.