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Category

Research

  • ChatGPT’s expanding world of work

    30 Oct
  • Working with academic communities to build scientific understanding

    30 Oct
  • Bringing GPT-Rosalind to academic research labs

    30 Oct
  • Sharing AI progress in mathematics

    30 Oct
  • Our framework for reporting model misalignment

    30 Oct
  • On the Navier–Stokes Millennium Prize Problem

    30 Oct
  • Research acceleration: The view inside OpenAI

    30 Oct
  • GPT-6 Astra: A new generation of intelligence

    30 Oct
  • Solving the solvent problem

    30 Oct
  • The benefits of medical AI assistance vary based on user expertise

    30 Oct
  • How enabling two settings tripled our scores on the ARC-AGI-3 benchmark

    30 Oct
  • Working to automate nuclear plant operations

    30 Oct
  • Working to automate nuclear plant operations

    30 Oct
  • Professor Emeritus Dimitri Bertsekas, influential computer scientist and prolific author, dies at 83

    30 Oct
  • A better way to turn 2D designs into 3D models for rapid prototyping

    30 Oct
  • 3 Questions: Neural transparency and the future of AI design

    30 Oct
  • Helping AI models to meet the real world

    30 Oct
  • Helping AI models to meet the real world

    30 Oct
  • AI agents create virtual playgrounds to help robots get crucial training data

    30 Oct
  • New method aims to keep kids safe from illegal AI-generated content

    30 Oct
  • Tiny robot boats build floating structures

    30 Oct
  • Separating signal from noise in coding evaluations

    30 Oct
  • How novice coders can develop AI programs for military applications

    30 Oct
  • How Open Models Are Driving AI Research

    30 Oct
  • MIT in the media: Innovating and educating for the next 250 years of America

    30 Oct
  • Introducing GeneBench-Pro

    30 Oct
  • LLMs help robots understand vague instructions and focus on key details

    30 Oct
  • MIT in the media: Exploring how curiosity-driven science is an essential ingredient in America’s success

    30 Oct
  • Improving the speed and energy-efficiency of AI agents

    30 Oct
  • New chip could help tiny robots traverse complex environments

    30 Oct
  • A better way to model the behavior of metal alloys

    30 Oct
  • MIT in the media: For the future of tech, « Massachusetts can absolutely lead »

    30 Oct
  • In game theory, generalists sometimes win out over specialists

    30 Oct
  • A near-autonomous AI chemist improves a challenging reaction in medicinal chemistry

    30 Oct
  • Could AI tell you where you left your keys?

    30 Oct
  • Introducing LifeSciBench

    30 Oct
  • Predicting model behavior before release by simulating deployment

    30 Oct
  • When it comes to predicting people’s preferences, it pays to consider “the power of three”

    30 Oct
  • The consequences of relying on AI for accurate news

    30 Oct
  • NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery

    30 Oct
  • Dreaming: Better memory for a more helpful ChatGPT

    30 Oct
  • Teaching AI agents to ask better questions by playing “Battleship”

    30 Oct
  • NVIDIA Research Unlocks Advanced Grasping, Smarter Autonomous Driving and Agent Training at Scale

    30 Oct
  • MIT researchers teach AI models to interpret charts

    30 Oct
  • Media Advisory: MIT to establish regional quantum hub

    30 Oct
  • NVIDIA Research Advances Robotics From Simulation to the Real World

    30 Oct
  • Technology usually creates jobs for young, skilled workers. Will AI do the same?

    30 Oct
  • An OpenAI model has disproved a central conjecture in discrete geometry

    30 Oct
  • What Parameter Golf taught us about AI-assisted research

    30 Oct
  • Powering the Next American Century: US Energy Secretary Chris Wright and NVIDIA’s Ian Buck on the Genesis Mission

    30 Oct
  • Study: Firms often use automation to control certain workers’ wages

    30 Oct
  • Making the case for curiosity-driven science

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

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

    30 Oct
  • Enabling privacy-preserving AI training on everyday devices

    30 Oct
  • A faster way to estimate AI power consumption

    30 Oct
  • Making Sense of the Early Universe

    30 Oct
  • Teaching AI models to say “I’m not sure”

    30 Oct
  • Introducing OpenAI Privacy Filter

    30 Oct
  • Introducing GPT-Rosalind for life sciences research

    30 Oct
  • Human-machine teaming dives underwater

    30 Oct
  • A philosophy of work

    30 Oct
  • New technique makes AI models leaner and faster while they’re still learning

    30 Oct
  • Helping data centers deliver higher performance with less hardware

    30 Oct
  • Evaluating the ethics of autonomous systems

    30 Oct
  • Preview tool helps makers visualize 3D-printed objects

    30 Oct
  • MIT researchers use AI to uncover atomic defects in materials

    30 Oct
  • MIT engineers design proteins by their motion, not just their shape

    30 Oct
  • AI system learns to keep warehouse robot traffic running smoothly

    30 Oct
  • Augmenting citizen science with computer vision for fish monitoring

    30 Oct
  • Wristband enables wearers to control a robotic hand with their own movements

    30 Oct
  • Inside our approach to the Model Spec

    30 Oct
  • How to create “humble” AI

    30 Oct
  • MIT and Hasso Plattner Institute establish collaborative hub for AI and creativity

    30 Oct
  • A better method for identifying overconfident large language models

    30 Oct
  • Generative AI improves a wireless vision system that sees through obstructions

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

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

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

    30 Oct
  • A better method for planning complex visual tasks

    30 Oct
  • Improving instruction hierarchy in frontier LLMs

    30 Oct
  • Improving AI models’ ability to explain their predictions

    30 Oct
  • Reasoning models struggle to control their chains of thought, and that’s good

    30 Oct
  • Extending single-minus amplitudes to gravitons

    30 Oct
  • A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster

    30 Oct
  • New method could increase LLM training efficiency

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

    30 Oct
  • AI to help researchers see the bigger picture in cell biology

    30 Oct
  • Enhancing maritime cybersecurity with technology and policy

    30 Oct
  • Our First Proof submissions

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

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

    30 Oct
  • Parking-aware navigation system could prevent frustration and emissions

    30 Oct
  • Personalization features can make LLMs more agreeable

    30 Oct
  • Introducing EVMbench

    30 Oct
  • GPT-5.2 derives a new result in theoretical physics

    30 Oct
  • New J-PAL research and policy initiative to test and scale AI innovations to fight poverty

    30 Oct
  • Accelerating science with AI and simulations

    30 Oct
  • Using synthetic biology and AI to address global antimicrobial resistance threat

    30 Oct
  • AI algorithm enables tracking of vital white matter pathways

    30 Oct

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