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.
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.
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.
Economics doctoral student Whitney Zhang investigates how technologies and organizational decisions shape labor markets.
With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
System developed at MIT could provide realistic predictions for a wide variety of reactions, while maintaining real-world physical constraints.
By visualizing Escher-like optical illusions in 2.5 dimensions, the “Meschers” tool could help scientists understand physics-defying shapes and spark new designs.
This new approach could lead to enhanced AI models for drug and materials discovery.
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.
A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.
Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.