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Computer science and technology

  • Human-machine teaming dives underwater

    16 Avr
  • New technique makes AI models leaner and faster while they’re still learning

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

    16 Avr
  • Helping data centers deliver higher performance with less hardware

    16 Avr
  • Preview tool helps makers visualize 3D-printed objects

    16 Avr
  • Seeing sounds

    16 Avr
  • Seeing sounds

    16 Avr
  • AI system learns to keep warehouse robot traffic running smoothly

    16 Avr
  • Augmenting citizen science with computer vision for fish monitoring

    16 Avr
  • A better method for identifying overconfident large language models

    16 Avr
  • Generative AI improves a wireless vision system that sees through obstructions

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

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

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

    16 Avr
  • A better method for planning complex visual tasks

    16 Avr
  • Improving AI models’ ability to explain their predictions

    16 Avr
  • A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster

    16 Avr
  • New method could increase LLM training efficiency

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

    16 Avr
  • AI to help researchers see the bigger picture in cell biology

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

    16 Avr
  • Parking-aware navigation system could prevent frustration and emissions

    16 Avr
  • Personalization features can make LLMs more agreeable

    16 Avr
  • Study: Platforms that rank the latest LLMs can be unreliable

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

    16 Avr
  • Brian Hedden named co-associate dean of Social and Ethical Responsibilities of Computing

    16 Avr
  • Antonio Torralba, three MIT alumni named 2025 ACM fellows

    16 Avr
  • 3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

    16 Avr
  • How generative AI can help scientists synthesize complex materials

    16 Avr
  • The philosophical puzzle of rational artificial intelligence

    16 Avr
  • Why it’s critical to move beyond overly aggregated machine-learning metrics

    16 Avr
  • Generative AI tool helps 3D print personal items that sustain daily use

    16 Avr
  • 3 Questions: How AI could optimize the power grid

    16 Avr
  • Decoding the Arctic to predict winter weather

    16 Avr
  • MIT scientists investigate memorization risk in the age of clinical AI

    16 Avr
  • MIT in the media: 2025 in review

    16 Avr
  • Guided learning lets “untrainable” neural networks realize their potential

    16 Avr
  • A new way to increase the capabilities of large language models

    16 Avr
  • A “scientific sandbox” lets researchers explore the evolution of vision systems

    16 Avr
  • “Robot, make me a chair”

    16 Avr
  • Enabling small language models to solve complex reasoning tasks

    16 Avr
  • New MIT program to train military leaders for the AI age

    16 Avr
  • New method improves the reliability of statistical estimations

    16 Avr
  • New materials could boost the energy efficiency of microelectronics

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

    16 Avr
  • A smarter way for large language models to think about hard problems

    16 Avr
  • New control system teaches soft robots the art of staying safe

    16 Avr
  • Researchers discover a shortcoming that makes LLMs less reliable

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

    16 Avr
  • The cost of thinking

    16 Avr
  • Understanding the nuances of human-like intelligence

    16 Avr
  • Charting the future of AI, from safer answers to faster thinking

    16 Avr
  • MIT researchers propose a new model for legible, modular software

    16 Avr
  • Teaching robots to map large environments

    16 Avr
  • 3 Questions: How AI is helping us monitor and support vulnerable ecosystems

    16 Avr
  • A faster problem-solving tool that guarantees feasibility

    16 Avr
  • The brain power behind sustainable AI

    16 Avr
  • Creating AI that matters

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

    16 Avr
  • Method teaches generative AI models to locate personalized objects

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

    16 Avr
  • Using generative AI to diversify virtual training grounds for robots

    16 Avr
  • Fighting for the health of the planet with AI

    16 Avr
  • AI maps how a new antibiotic targets gut bacteria

    16 Avr
  • Responding to the climate impact of generative AI

    16 Avr
  • New AI system could accelerate clinical research

    16 Avr
  • MIT affiliates win AI for Math grants to accelerate mathematical discovery

    16 Avr
  • What does the future hold for generative AI?

    16 Avr
  • How to build AI scaling laws for efficient LLM training and budget maximization

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

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

    16 Avr
  • A greener way to 3D print stronger stuff

    16 Avr
  • A new generative AI approach to predicting chemical reactions

    16 Avr
  • 3 Questions: The pros and cons of synthetic data in AI

    16 Avr
  • MIT researchers develop AI tool to improve flu vaccine strain selection

    16 Avr
  • A new model predicts how molecules will dissolve in different solvents

    16 Avr
  • Eco-driving measures could significantly reduce vehicle emissions

    16 Avr
  • Helping data storage keep up with the AI revolution

    16 Avr
  • MIT tool visualizes and edits “physically impossible” objects

    16 Avr
  • New algorithms enable efficient machine learning with symmetric data

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

    16 Avr
  • A new way to edit or generate images

    16 Avr
  • The unique, mathematical shortcuts language models use to predict dynamic scenarios

    16 Avr
  • This “smart coach” helps LLMs switch between text and code

    16 Avr
  • Can AI really code? Study maps the roadblocks to autonomous software engineering

    16 Avr
  • How to more efficiently study complex treatment interactions

    16 Avr
  • AI shapes autonomous underwater “gliders”

    16 Avr
  • Study could lead to LLMs that are better at complex reasoning

    16 Avr
  • Robotic probe quickly measures key properties of new materials

    16 Avr
  • Using generative AI to help robots jump higher and land safely

    16 Avr
  • LLMs factor in unrelated information when recommending medical treatments

    16 Avr
  • Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

    16 Avr
  • Unpacking the bias of large language models

    16 Avr
  • A sounding board for strengthening the student experience

    16 Avr
  • Photonic processor could streamline 6G wireless signal processing

    16 Avr
  • Inroads to personalized AI trip planning

    16 Avr
  • Melding data, systems, and society

    16 Avr
  • How we really judge AI

    16 Avr
  • AI-enabled control system helps autonomous drones stay on target in uncertain environments

    16 Avr
  • Envisioning a future where health care tech leaves some behind

    16 Avr

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