Inroads to personalized AI trip planning
A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.
A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.
“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.
Lincoln Laboratory is transitioning tools to the 618th Air Operations Center to streamline global transport logistics.
By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.
The MIT Advanced Vehicle Technology Consortium provides data-driven insights into driver behavior, along with trust in AI and advance vehicle technology.