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.
Algorithms
Training LLMs to self-detoxify their language
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.
New method efficiently safeguards sensitive AI training data
The approach maintains an AI model’s accuracy while ensuring attackers can’t extract secret information.
Researchers teach LLMs to solve complex planning challenges
This new framework leverages a model’s reasoning abilities to create a “smart assistant” that finds the optimal solution to multistep problems.
Robotic helper making mistakes? Just nudge it in the right direction
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.
MIT spinout maps the body’s metabolites to uncover the hidden drivers of disease
ReviveMed uses AI to gather large-scale data on metabolites — molecules like lipids, cholesterol, and sugar — to match patients with therapeutics.
Like human brains, large language models reason about diverse data in a general way
A new study shows LLMs represent different data types based on their underlying meaning and reason about data in their dominant language.
AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Puzzling out climate change
Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.
Streamlining data collection for improved salmon population management
Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.