- 1 Universal AI is “a pathway to AI fluency that’s accessible and approachable to anyone, anywhere” ↗
- 2 Games people — and machines — play: Untangling strategic reasoning to advance AI ↗
- 3 Beacon Biosignals is mapping the brain during sleep ↗
- 4 Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models ↗
- 5 The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing ↗
- 6 Enabling privacy-preserving AI training on everyday devices ↗
- 7 A faster way to estimate AI power consumption ↗
- 8 MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone ↗
- 9 Teaching AI models to say “I’m not sure” ↗
- 10 Jacob Andreas and Brett McGuire named Edgerton Award winners ↗
- 11 Bringing AI-driven protein-design tools to biologists everywhere ↗
- 12 Human-machine teaming dives underwater ↗
- 13 New technique makes AI models leaner and faster while they’re still learning ↗
- 14 Helping data centers deliver higher performance with less hardware ↗
- 15 Working to advance the nuclear renaissance ↗
- 16 Evaluating the ethics of autonomous systems ↗
- 17 Preview tool helps makers visualize 3D-printed objects ↗
- 18 Building the blocks of life ↗
- 19 MIT researchers use AI to uncover atomic defects in materials ↗
- 20 AI system learns to keep warehouse robot traffic running smoothly ↗
- 21 Augmenting citizen science with computer vision for fish monitoring ↗
- 22 Wristband enables wearers to control a robotic hand with their own movements ↗
- 23 A better method for identifying overconfident large language models ↗
- 24 Generative AI improves a wireless vision system that sees through obstructions ↗
- 25 MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact ↗
- 26 Can AI help predict which heart-failure patients will worsen within a year? ↗
- 27 3 Questions: On the future of AI and the mathematical and physical sciences ↗
- 28 A better method for planning complex visual tasks ↗
- 29 3 Questions: Building predictive models to characterize tumor progression ↗
- 30 How Joseph Paradiso’s sensing innovations bridge the arts, medicine, and ecology ↗
- 31 Neurons receive precisely tailored teaching signals as we learn ↗
- 32 Improving AI models’ ability to explain their predictions ↗
- 33 A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster ↗
- 34 New method could increase LLM training efficiency ↗
- 35 AI to help researchers see the bigger picture in cell biology ↗
- 36 Study: AI chatbots provide less-accurate information to vulnerable users ↗
- 37 Exposing biases, moods, personalities, and abstract concepts hidden in large language models ↗
- 38 Parking-aware navigation system could prevent frustration and emissions ↗
- 39 Personalization features can make LLMs more agreeable ↗
- 40 Accelerating science with AI and simulations ↗
- 41 Study: Platforms that rank the latest LLMs can be unreliable ↗
- 42 Helping AI agents search to get the best results out of large language models ↗
- 43 How generative AI can help scientists synthesize complex materials ↗
- 44 The philosophical puzzle of rational artificial intelligence ↗
- 45 Biology-based brain model matches animals in learning, enables new discovery ↗
- 46 Why it’s critical to move beyond overly aggregated machine-learning metrics ↗
- 47 Generative AI tool helps 3D print personal items that sustain daily use ↗
- 48 3 Questions: How AI could optimize the power grid ↗
- 49 A “scientific sandbox” lets researchers explore the evolution of vision systems ↗
- 50 “Robot, make me a chair” ↗