National Science Foundation (NSF)
National Science Foundation (NSF)

Teaching robots to map large environments

A new approach developed at MIT could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.

Improving the workplace of the future

Economics doctoral student Whitney Zhang investigates how technologies and organizational decisions shape labor markets.

New tool makes generative AI models more likely to create breakthrough materials

With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.

A new generative AI approach to predicting chemical reactions

System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.

MIT tool visualizes and edits “physically impossible” objects

By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.

New algorithms enable efficient machine learning with symmetric data

This new approach could lead to enhanced AI models for drug and materials discovery.

The unique, mathematical shortcuts language models use to predict dynamic scenarios

Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.

Can AI really code? Study maps the roadblocks to autonomous software engineering

A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.

Study could lead to LLMs that are better at complex reasoning

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.