MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

MIT Schwarzman College of Computing

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

AI accelerates problem-solving in complex scenarios

A new, data-driven approach could lead to better solutions for tricky optimization problems like global package routing or power grid operation.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Faculty machine learning MIT Schwarzman College of Computing School of Engineering Special events and guest speakers Staff Students

What does the future hold for generative AI?

Rodney Brooks, co-founder of iRobot, kicks off an MIT symposium on the promise and potential pitfalls of increasingly powerful AI tools like ChatGPT.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Human-computer interaction machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Robots

New method uses crowdsourced feedback to help train robots

Human Guided Exploration (HuGE) enables AI agents to learn quickly with some help from humans, even if the humans make mistakes.

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Students pitch transformative ideas in generative AI at MIT Ignite competition

Twelve teams of students and postdocs across the MIT community presented innovative startup ideas with potential for real-world impact.

Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Electrical Engineering & Computer Science (eecs) image processing machine learning MIT Schwarzman College of Computing Research School of Engineering

Synthetic imagery sets new bar in AI training efficiency

MIT CSAIL researchers innovate with synthetic imagery to train AI, paving the way for more efficient and bias-reduced machine learning.

Algorithms Artificial Intelligence Computer science and technology Data Electrical Engineering & Computer Science (eecs) Internet Of Things machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Mobile devices National Science Foundation (NSF) Privacy Research School of Engineering

Technique enables AI on edge devices to keep learning over time

With the PockEngine training method, machine-learning models can efficiently and continuously learn from user data on edge devices like smartphones.

3-D printing Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) computer-vision Defense Advanced Research Projects Agency (DARPA) Electrical Engineering & Computer Science (eecs) machine learning Materials science and engineering MIT Schwarzman College of Computing National Science Foundation (NSF) Research Robots School of Engineering

This 3D printer can watch itself fabricate objects

Computer vision enables contact-free 3D printing, letting engineers print with high-performance materials they couldn’t use before.

Artificial Intelligence Arts Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) Ethics Human-computer interaction IDSS Labor and jobs Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing School of Engineering

Explained: Generative AI

How do powerful generative AI systems like ChatGPT work, and what makes them different from other types of artificial intelligence?

Algorithms Artificial Intelligence Brain and cognitive sciences Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical Engineering & Computer Science (eecs) Imaging machine learning Microscopy MIT Schwarzman College of Computing Nanoscience and nanotechnology Neurons Neuroscience Research School of Engineering Synapses

Using AI to optimize for rapid neural imaging

MIT CSAIL researchers combine AI and electron microscopy to expedite detailed brain network mapping, aiming to enhance connectomics research and clinical pathology.

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Accelerating AI tasks while preserving data security

The SecureLoop search tool efficiently identifies secure designs for hardware that can boost the performance of complex AI tasks, while requiring less energy.