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MIT News - Artificial intelligence

• MIT’s McGovern Institute is shaping brain science and improving human lives on a global scale
• Making AI-generated code more accurate in any language
• A faster way to solve complex planning problems
• Training LLMs to self-detoxify their language
• New method efficiently safeguards sensitive AI training data
• Could LLMs help design our next medicines and materials?
• New method assesses and improves the reliability of radiologists’ diagnostic reports
• Taking the “training wheels” off clean energy
• Vana is letting users own a piece of the AI models trained on their data
• Researchers teach LLMs to solve complex planning challenges
• Pattie Maes receives ACM SIGCHI Lifetime Research Award
• For this computer scientist, MIT Open Learning was the start of a life-changing journey
• Making higher education more accessible to students in Pakistan
• MIT Maritime Consortium sets sail
• AI tool generates high-quality images faster than state-of-the-art approaches
• At the core of problem-solving
• “An AI future that honors dignity for everyone”
• Making airfield assessments automatic, remote, and safe
• Robotic helper making mistakes? Just nudge it in the right direction
• 3 Questions: Visualizing research in the age of AI
• Markus Buehler receives 2025 Washington Award
• Collaborating to advance research and innovation on essential chips for AI
• An ancient RNA-guided system could simplify delivery of gene editing therapies
• AI system predicts protein fragments that can bind to or inhibit a target
• Like human brains, large language models reason about diverse data in a general way
• MIT spinout maps the body’s metabolites to uncover the hidden drivers of disease
• AI model deciphers the code in proteins that tells them where to go
• Gift from Sebastian Man ’79, SM ’80 supports MIT Stephen A. Schwarzman College of Computing building
• Bridging philosophy and AI to explore computing ethics
• Puzzling out climate change
• Can deep learning transform heart failure prevention?
• Creating a common language
• Validation technique could help scientists make more accurate forecasts
• Streamlining data collection for improved salmon population management
• Aligning AI with human values
• Introducing the MIT Generative AI Impact Consortium
• User-friendly system can help developers build more efficient simulations and AI models
• With generative AI, MIT chemists quickly calculate 3D genomic structures
• 3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities
• MIT students' works redefine human-AI collaboration
• New training approach could help AI agents perform better in uncertain conditions
• Expanding robot perception
• A platform to expedite clean energy projects
• Toward video generative models of the molecular world
• The multifaceted challenge of powering AI
• Explained: Generative AI’s environmental impact
• Algorithms and AI for a better world
• Making the art world more accessible
• New computational chemistry techniques accelerate the prediction of molecules and materials
• For healthy hearing, timing matters
• Q&A: The climate impact of generative AI
• Teaching AI to communicate sounds like humans do
• A new computational model can predict antibody structures more accurately
• Unlocking the hidden power of boiling — for energy, space, and beyond
• Ecologists find computer vision models’ blind spots in retrieving wildlife images
• Startup’s autonomous drones precisely track warehouse inventories
• MIT welcomes Frida Polli as its next visiting innovation scholar
• Need a research hypothesis? Ask AI.
• MIT engineers grow “high-rise” 3D chips
• When MIT’s interdisciplinary NEET program is a perfect fit
• MIT researchers introduce Boltz-1, a fully open-source model for predicting biomolecular structures
• Lara Ozkan named 2025 Marshall Scholar
• MIT affiliates named 2024 Schmidt Sciences AI2050 Fellows
• Researchers reduce bias in AI models while preserving or improving accuracy
• Enabling AI to explain its predictions in plain language
• Daniela Rus wins John Scott Award
• Citation tool offers a new approach to trustworthy AI-generated content
• What do we know about the economics of AI?
• Study: Browsing negative content online makes mental health struggles worse
• Want to design the car of the future? Here are 8,000 designs to get you started.
• MIT delegation mainstreams biodiversity conservation at the UN Biodiversity Convention, COP16
• A new way to create realistic 3D shapes using generative AI
• Photonic processor could enable ultrafast AI computations with extreme energy efficiency
• A data designer driven to collaborate with communities
• Improving health, one machine learning system at a time
• New AI tool generates realistic satellite images of future flooding
• Building an understanding of how drivers interact with emerging vehicle technologies
• A vision for U.S. science success
• MIT researchers develop an efficient way to train more reliable AI agents
• Advancing urban tree monitoring with AI-powered digital twins
• A model of virtuosity
• Can robots learn from machine dreams?
• Four from MIT named 2025 Rhodes Scholars
• Ensuring a durable transition
• Graph-based AI model maps the future of innovation
• 3 Questions: Inverting the problem of design
• A causal theory for studying the cause-and-effect relationships of genes
• A portable light system that can digitize everyday objects
• Despite its impressive output, generative AI doesn’t have a coherent understanding of the world
• Empowering systemic racism research at MIT and beyond
• Artist and designer Es Devlin awarded Eugene McDermott Award in the Arts at MIT
• Nanoscale transistors could enable more efficient electronics
• MIT Schwarzman College of Computing launches postdoctoral program to advance AI across disciplines
• A faster, better way to train general-purpose robots
• Making it easier to verify an AI model’s responses
• Combining next-token prediction and video diffusion in computer vision and robotics
• Equipping doctors with AI co-pilots
• Artificial intelligence meets “blisk” in new DARPA-funded collaboration
• Modeling relationships to solve complex problems efficiently
• How AI is improving simulations with smarter sampling techniques