AI tool generates high-quality images faster than state-of-the-art approaches
Researchers fuse the best of two popular methods to create an image generator that uses less energy and can run locally on a laptop or smartphone.
MIT faculty, alumni named 2025 Sloan Research Fellows
Annual award honors early-career researchers for creativity, innovation, and research accomplishments.
Like human brains, large language models reason about diverse data in a general way
A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.
A new way to create realistic 3D shapes using generative AI
Researchers propose a simple fix to an existing technique that could help artists, designers, and engineers create better 3D models.
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.
Enhancing LLM collaboration for smarter, more efficient solutions
“Co-LLM” algorithm helps a general-purpose AI model collaborate with an expert large language model by combining the best parts of both answers, leading to more factual responses.
A framework for solving parabolic partial differential equations
A new algorithm solves complicated partial differential equations by breaking them down into simpler problems, potentially guiding computer graphics and geometry processing.
Method prevents an AI model from being overconfident about wrong answers
More efficient than other approaches, the “Thermometer” technique could help someone know when they should trust a large language model.
MIT researchers advance automated interpretability in AI models
MAIA is a multimodal agent that can iteratively design experiments to better understand various components of AI systems.
Reasoning skills of large language models are often overestimated
New CSAIL research highlights how LLMs excel in familiar scenarios but struggle in novel ones, questioning their true reasoning abilities versus reliance on memorization.
Understanding the visual knowledge of language models
LLMs trained primarily on text can generate complex visual concepts through code with self-correction. Researchers used these illustrations to train an image-free computer vision system to recognize real photos.
Researchers use large language models to help robots navigate
The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.
Looking for a specific action in a video? This AI-based method can find it for you
A new approach could streamline virtual training processes or aid clinicians in reviewing diagnostic videos.
Using ideas from game theory to improve the reliability of language models
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.