Electrical engineering and computer science (EECS)

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3 Questions: Using computation to study the world’s best single-celled chemists

Artificial Intelligence, Bacteria, Biology, Electrical engineering and computer science (EECS), Evolution, Faculty, Genetics, Interview, Machine Learning, Microbes, MIT Schwarzman College of Computing, School of Engineering, School of Science

Today, out of an estimated 1 trillion species on Earth, 99.999 percent are considered microbial — bacteria, archaea, viruses, and single-celled eukaryotes. For much of our planet’s history, microbes ruled the Earth, able to live and thrive in the most extreme of environments. Researchers have only just begun in the last few decades to contend […]

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Enabling small language models to solve complex reasoning tasks

Algorithms, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Machine Learning, MIT Schwarzman College of Computing, MIT Siegel Family Quest for Intelligence, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, School of Science

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a wide margin on complex tasks. Try playing Sudoku with one, for instance, where you fill in numbers one through nine in such

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New MIT program to train military leaders for the AI age

Artificial Intelligence, Classes and programs, Computer science and technology, cybersecurity, Department of Defense (DoD), Electrical engineering and computer science (EECS), Logistics, Mechanical engineering, MIT Schwarzman College of Computing, Navy, Oceanography and ocean engineering, School of Engineering, Security studies and military, Supply chains

Artificial intelligence can enhance decision-making and enable action with reduced risk and greater precision, making it a critical tool for national security. A new program offered jointly by the MIT departments of Mechanical Engineering (Course 2, MechE) and Electrical Engineering and Computer Science (Course 6, EECS) will provide breadth and depth in technical studies for

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New method improves the reliability of statistical estimations

Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mathematics, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering

Let’s say an environmental scientist is studying whether exposure to air pollution is associated with lower birth weights in a particular county.They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships.Standard machine-learning methods excel at making predictions and sometimes provide uncertainties, like

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New materials could boost the energy efficiency of microelectronics

Artificial Intelligence, Computer chips, Computer science and technology, Electrical engineering and computer science (EECS), Electronics, Energy, Materials science and engineering, Microsystems Technology Laboratories, MIT Schwarzman College of Computing, MIT.nano, Nanoscience and nanotechnology, Research, School of Engineering, Sustainable computing

MIT researchers have developed a new fabrication method that could enable the production of more energy efficient electronics by stacking multiple functional components on top of one existing circuit.In traditional circuits, logic devices that perform computation, like transistors, and memory devices that store data are built as separate components, forcing data to travel back and

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MIT affiliates named 2025 Schmidt Sciences AI2050 Fellows

Algorithms, Artificial Intelligence, Awards, honors and fellowships, Economics, Electrical engineering and computer science (EECS), Faculty, Graduate, postdoctoral, MIT Schwarzman College of Computing, Research Laboratory of Electronics, School of Engineering, School of Humanities Arts and Social Sciences, Staff

Two current MIT affiliates and seven additional alumni are among those named to the 2025 cohort of AI2050 Fellows.  Zongyi Li, a postdoc in the MIT Computer Science and Artificial Intelligence Lab, and Tess Smidt ’12, an associate professor of electrical engineering and computer science (EECS), were both named as AI2050 Early Career Fellows. Seven additional MIT

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MIT researchers “speak objects into existence” using AI and robotics

Architecture, Artificial Intelligence, Center for Bits and Atoms, Computer science and technology, Design, Electrical engineering and computer science (EECS), Fabrication, Human-computer interaction, Mechanical engineering, MIT Morningside Academy for Design, MIT Schwarzman College of Computing, Natural Language Processing, Research, Robotics, School of Architecture and Planning, School of Engineering

Generative AI and robotics are moving us ever closer to the day when we can ask for an object and have it created within a few minutes. In fact, MIT researchers have developed a speech-to-reality system, an AI-driven workflow that allows them to provide input to a robotic arm and “speak objects into existence,” creating

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Robots that spare warehouse workers the heavy lifting

Alumni/ae, Artificial Intelligence, Electrical engineering and computer science (EECS), Innovation and Entrepreneurship (I&E), Machine Learning, Robotics, School of Engineering, Startups

There are some jobs human bodies just weren’t meant to do. Unloading trucks and shipping containers is a repetitive, grueling task — and a big reason warehouse injury rates are more than twice the national average.The Pickle Robot Company wants its machines to do the heavy lifting. The company’s one-armed robots autonomously unload trailers, picking

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A smarter way for large language models to think about hard problems

Algorithms, Artificial Intelligence, Computer science and technology, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Research, School of Engineering

To make large language models (LLMs) more accurate when answering harder questions, researchers can let the model spend more time thinking about potential solutions.But common approaches that give LLMs this capability set a fixed computational budget for every problem, regardless of how complex it is. This means the LLM might waste computational resources on simpler questions

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MIT engineers design an aerial microrobot that can fly as fast as a bumblebee

Aeronautical and astronautical engineering, Artificial Intelligence, Bioinspiration, Drones, Electrical engineering and computer science (EECS), Electronics, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Research Laboratory of Electronics, Robotics, School of Engineering

In the future, tiny flying robots could be deployed to aid in the search for survivors trapped beneath the rubble after a devastating earthquake. Like real insects, these robots could flit through tight spaces larger robots can’t reach, while simultaneously dodging stationary obstacles and pieces of falling rubble.So far, aerial microrobots have only been able

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