Algorithms
Algorithms

Algorithms

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.

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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Generating opportunities with generative AI

Rama Ramakrishnan helps companies explore the promises and perils of large language models and other transformative AI technologies.

Aircraft Algorithms Artificial Intelligence Aviation Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Distributed Robotics Laboratory Drones Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Networks Research Robotics School of Engineering

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

Aircraft Algorithms Artificial Intelligence Aviation Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Distributed Robotics Laboratory Drones Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Networks Research Robotics School of Engineering

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

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MIT scholars awarded seed grants to probe the social implications of generative AI

The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.

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

Multi-AI collaboration helps reasoning and factual accuracy in large language models

Researchers use multiple AI models to collaborate, debate, and improve their reasoning abilities to advance the performance of LLMs while increasing accountability and factual accuracy.

Algorithms Anthropology Archeology Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical engineering and computer science (EECS) Ethics Health sciences and technology Institute for Medical Engineering and Science (IMES) Jameel Clinic machine learning Medicine MIT Schwarzman College of Computing National Institutes of Health (NIH) Public health Race and gender Research School of Engineering Technology and society

How an archeological approach can help leverage biased data in AI to improve medicine

Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.

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AI pilot programs look to reduce energy use and emissions on MIT campus

A cross-departmental team is leading efforts to utilize machine learning for increased efficiency in heating and cooling MIT’s buildings.

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Autonomous innovations in an uncertain world

Jonathan How and his team at the Aerospace Controls Laboratory develop planning algorithms that allow autonomous vehicles to navigate dynamic environments without colliding.