A faster way to solve complex planning problems
By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.
By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.
A new method from the MIT-IBM Watson AI Lab helps large language models to steer their own responses toward safer, more ethical, value-aligned outputs.
The approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.
This new framework leverages a model’s reasoning abilities to create a “smart assistant” that finds the optimal solution to multistep problems.
New research could allow a person to correct a robot’s actions in real-time, using the kind of feedback they’d give another human.
ReviveMed uses AI to gather large-scale data on metabolites — molecules like lipids, cholesterol, and sugar — to match patients with therapeutics.
A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.