machine learning
machine learning

machine learning

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Bringing the social and ethical responsibilities of computing to the forefront

The inaugural SERC Symposium convened experts from multiple disciplines to explore the challenges and opportunities that arise with the broad applicability of computing in many aspects of society.

Artificial Intelligence Biological engineering Broad Institute Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Drug discovery Electrical engineering and computer science (EECS) machine learning Mathematics MIT Schwarzman College of Computing National Institutes of Health (NIH) National Science Foundation (NSF) Proteins Ragon Institute Research School of Engineering School of Science

New model offers a way to speed up drug discovery

By applying a language model to protein-drug interactions, researchers can quickly screen large libraries of potential drug compounds.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) machine learning MIT Schwarzman College of Computing Natural language processing Research School of Engineering

MIT researchers make language models scalable self-learners

The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.