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Category

Computer science and technology

  • Building AI models that understand chemical principles

    21 Mai
  • Justin Solomon appointed associate dean of engineering education

    21 Mai
  • Games people — and machines — play: Untangling strategic reasoning to advance AI

    21 Mai
  • Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models

    21 Mai
  • The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing

    21 Mai
  • Enabling privacy-preserving AI training on everyday devices

    21 Mai
  • A faster way to estimate AI power consumption

    21 Mai
  • MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone

    21 Mai
  • Teaching AI models to say “I’m not sure”

    21 Mai
  • Human-machine teaming dives underwater

    21 Mai
  • New technique makes AI models leaner and faster while they’re still learning

    21 Mai
  • Sixteen new START.nano companies are developing hard-tech solutions with the support of MIT.nano

    21 Mai
  • Helping data centers deliver higher performance with less hardware

    21 Mai
  • Preview tool helps makers visualize 3D-printed objects

    21 Mai
  • Seeing sounds

    21 Mai
  • Seeing sounds

    21 Mai
  • AI system learns to keep warehouse robot traffic running smoothly

    21 Mai
  • Augmenting citizen science with computer vision for fish monitoring

    21 Mai
  • A better method for identifying overconfident large language models

    21 Mai
  • Generative AI improves a wireless vision system that sees through obstructions

    21 Mai
  • MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact

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

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

    21 Mai
  • A better method for planning complex visual tasks

    21 Mai
  • Improving AI models’ ability to explain their predictions

    21 Mai
  • A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster

    21 Mai
  • New method could increase LLM training efficiency

    21 Mai
  • Mixing generative AI with physics to create personal items that work in the real world

    21 Mai
  • AI to help researchers see the bigger picture in cell biology

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

    21 Mai
  • Parking-aware navigation system could prevent frustration and emissions

    21 Mai
  • Personalization features can make LLMs more agreeable

    21 Mai
  • Study: Platforms that rank the latest LLMs can be unreliable

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

    21 Mai
  • Brian Hedden named co-associate dean of Social and Ethical Responsibilities of Computing

    21 Mai
  • Antonio Torralba, three MIT alumni named 2025 ACM fellows

    21 Mai
  • 3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

    21 Mai
  • How generative AI can help scientists synthesize complex materials

    21 Mai
  • The philosophical puzzle of rational artificial intelligence

    21 Mai
  • Why it’s critical to move beyond overly aggregated machine-learning metrics

    21 Mai
  • Generative AI tool helps 3D print personal items that sustain daily use

    21 Mai
  • 3 Questions: How AI could optimize the power grid

    21 Mai
  • Decoding the Arctic to predict winter weather

    21 Mai
  • MIT scientists investigate memorization risk in the age of clinical AI

    21 Mai
  • MIT in the media: 2025 in review

    21 Mai
  • Guided learning lets “untrainable” neural networks realize their potential

    21 Mai
  • A new way to increase the capabilities of large language models

    21 Mai
  • A “scientific sandbox” lets researchers explore the evolution of vision systems

    21 Mai
  • “Robot, make me a chair”

    21 Mai
  • Enabling small language models to solve complex reasoning tasks

    21 Mai
  • New MIT program to train military leaders for the AI age

    21 Mai
  • New method improves the reliability of statistical estimations

    21 Mai
  • New materials could boost the energy efficiency of microelectronics

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

    21 Mai
  • A smarter way for large language models to think about hard problems

    21 Mai
  • New control system teaches soft robots the art of staying safe

    21 Mai
  • Researchers discover a shortcoming that makes LLMs less reliable

    21 Mai
  • MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases

    21 Mai
  • The cost of thinking

    21 Mai
  • Understanding the nuances of human-like intelligence

    21 Mai
  • Charting the future of AI, from safer answers to faster thinking

    21 Mai
  • MIT researchers propose a new model for legible, modular software

    21 Mai
  • Teaching robots to map large environments

    21 Mai
  • 3 Questions: How AI is helping us monitor and support vulnerable ecosystems

    21 Mai
  • A faster problem-solving tool that guarantees feasibility

    21 Mai
  • The brain power behind sustainable AI

    21 Mai
  • Creating AI that matters

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

    21 Mai
  • Method teaches generative AI models to locate personalized objects

    21 Mai
  • MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI

    21 Mai
  • Using generative AI to diversify virtual training grounds for robots

    21 Mai
  • Fighting for the health of the planet with AI

    21 Mai
  • AI maps how a new antibiotic targets gut bacteria

    21 Mai
  • Responding to the climate impact of generative AI

    21 Mai
  • New AI system could accelerate clinical research

    21 Mai
  • MIT affiliates win AI for Math grants to accelerate mathematical discovery

    21 Mai
  • What does the future hold for generative AI?

    21 Mai
  • How to build AI scaling laws for efficient LLM training and budget maximization

    21 Mai
  • Machine-learning tool gives doctors a more detailed 3D picture of fetal health

    21 Mai
  • DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions

    21 Mai
  • A greener way to 3D print stronger stuff

    21 Mai
  • A new generative AI approach to predicting chemical reactions

    21 Mai
  • 3 Questions: The pros and cons of synthetic data in AI

    21 Mai
  • MIT researchers develop AI tool to improve flu vaccine strain selection

    21 Mai
  • A new model predicts how molecules will dissolve in different solvents

    21 Mai
  • Eco-driving measures could significantly reduce vehicle emissions

    21 Mai
  • Helping data storage keep up with the AI revolution

    21 Mai
  • MIT tool visualizes and edits “physically impossible” objects

    21 Mai
  • New algorithms enable efficient machine learning with symmetric data

    21 Mai
  • Robot, know thyself: New vision-based system teaches machines to understand their bodies

    21 Mai
  • A new way to edit or generate images

    21 Mai
  • The unique, mathematical shortcuts language models use to predict dynamic scenarios

    21 Mai
  • This “smart coach” helps LLMs switch between text and code

    21 Mai
  • Can AI really code? Study maps the roadblocks to autonomous software engineering

    21 Mai
  • How to more efficiently study complex treatment interactions

    21 Mai
  • AI shapes autonomous underwater “gliders”

    21 Mai
  • Study could lead to LLMs that are better at complex reasoning

    21 Mai
  • Robotic probe quickly measures key properties of new materials

    21 Mai
  • Using generative AI to help robots jump higher and land safely

    21 Mai
  • LLMs factor in unrelated information when recommending medical treatments

    21 Mai

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