MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

MIT Schwarzman College of Computing

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Can AI really code? Study maps the roadblocks to autonomous software engineering

A team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.

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How to more efficiently study complex treatment interactions

A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.

Artificial Intelligence Communications Electrical engineering and computer science (EECS) Health Care Institute for Medical Engineering and Science (IMES) Languages Lincoln Laboratory MIT Schwarzman College of Computing School of Engineering School of Humanities Arts and Social Sciences Technology and society

Changing the conversation in health care

The Language/AI Incubator, an MIT Human Insight Collaborative project, is investigating how AI can improve communications among patients and practitioners.

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AI shapes autonomous underwater “gliders”

An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab National Science Foundation (NSF) Research School of Engineering

Study could lead to LLMs that are better at complex reasoning

Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.

3-D printing Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Design Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering School of Science

Using generative AI to help robots jump higher and land safely

MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.

Artificial Intelligence Computer science and technology Diagnostics Electrical engineering and computer science (EECS) health Health Care Human-computer interaction Institute for Medical Engineering and Science (IMES) Laboratory for Information and Decision Systems (LIDS) machine learning Medicine MIT Schwarzman College of Computing Research School of Engineering Technology and society

LLMs factor in unrelated information when recommending medical treatments

Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.

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Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event

Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.

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A sounding board for strengthening the student experience

Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.

Algorithms Artificial Intelligence Civil and environmental engineering Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

Unpacking the bias of large language models

In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.