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

MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

With insect-like speed and agility, the tiny robot could someday aid in search-and-rescue missions.

Researchers discover a shortcoming that makes LLMs less reliable

Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.

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.