Computer science and technology
Computer science and technology

Computer science and technology

Algorithms Artificial Intelligence Business and management Computer science and technology Data Electrical engineering and computer science (EECS) Faculty IDSS Innovation and Entrepreneurship (I&E) Laboratory for Information and Decision Systems (LIDS) MIT intellectual property MIT Schwarzman College of Computing Profile Research School of Engineering Startups

Helping AI models to meet the real world

Through research and entrepreneurship, Professor Devavrat Shah is helping to design methods that can handle constant decision-making using limited computational resources.

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How MIT students are helping to prevent cyberattacks

Students from the MIT Cybersecurity Clinic help local governments and other vulnerable organizations defend against digital threats.

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AI agents create virtual playgrounds to help robots get crucial training data

“SceneSmith” system uses collaborative AI agents to create realistic 3D environments of places like kitchens, hotels, and living rooms, where robots can simulate everyday chores.

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New method aims to keep kids safe from illegal AI-generated content

Researchers developed an auditing technique to test generative AI models for malicious capabilities, without prompting them for illegal outputs.

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Tiny robot boats build floating structures

MIT researchers developed FloatForm, a swarm of small aquatic robots that snap together like ants forming a raft, assembling into reconfigurable structures on the water.

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How novice coders can develop AI programs for military applications

A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Human-computer interaction Interview machine learning MIT Schwarzman College of Computing School of Engineering

Q&A: What is agentic AI today, and what do we want it to be?

Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.

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3 Questions: Beyond data-driven aesthetics

In a new Keller Gallery exhibition, Alexandros Haridis SM ’17, PhD ’22 traces centuries of ideas about aesthetic judgment and explores how design can make complex computational systems visible.

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LLMs help robots understand vague instructions and focus on key details

To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.

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Improving the speed and energy-efficiency of AI agents

A new system, known as Murakkab, optimizes the design and deployment of multistep workflows that power AI applications.