Advancing urban tree monitoring with AI-powered digital twins
The Tree-D Fusion system integrates generative AI and genus-conditioned algorithms to create precise simulation-ready models of 600,000 existing urban trees across North America.
Research
Can robots learn from machine dreams?
MIT CSAIL researchers used AI-generated images to train a robot dog in parkour, without real-world data. Their LucidSim system demonstrates generative AI's potential for creating robotics training data.
Graph-based AI model maps the future of innovation
An AI method developed by Professor Markus Buehler finds hidden links between science and art to suggest novel materials.
3 Questions: Inverting the problem of design
MIT and IBM researchers are creating linkage mechanisms to innovate human-AI kinematic engineering.
A causal theory for studying the cause-and-effect relationships of genes
By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.
A portable light system that can digitize everyday objects
A new design tool uses UV and RGB lights to change the color and textures of everyday objects. The system could enable surfaces to display dynamic patterns, such as health…
Despite its impressive output, generative AI doesn’t have a coherent understanding of the world
Researchers show that even the best-performing large language models don’t form a true model of the world and its rules, and can thus fail unexpectedly on similar tasks.
Empowering systemic racism research at MIT and beyond
Researchers in the MIT Initiative on Combatting Systemic Racism are building an open data repository to advance research on racial inequity in domains like policing, housing, and health care.
Nanoscale transistors could enable more efficient electronics
Researchers are leveraging quantum mechanical properties to overcome the limits of silicon semiconductor technology.
A faster, better way to train general-purpose robots
Inspired by large language models, researchers develop a training technique that pools diverse data to teach robots new skills.