“Periodic table of machine learning” could fuel AI discovery
Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create new ones.
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Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create new ones.
A new technique automatically guides an LLM toward outputs that adhere to the rules of whatever programming language or other format is being used.
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.