Electrical engineering and computer science (EECS)

Auto Added by WPeMatico

Helping data centers deliver higher performance with less hardware

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, data, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), Electronics, Machine Learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, Sustainability

To improve data center efficiency, multiple storage devices are often pooled together over a network so many applications can share them. But even with pooling, significant device capacity remains underutilized due to performance variability across the devices.MIT researchers have now developed a system that boosts the performance of storage devices by handling three major sources […]

Helping data centers deliver higher performance with less hardware Read More »

Evaluating the ethics of autonomous systems

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Defense Advanced Research Projects Agency (DARPA), Electrical engineering and computer science (EECS), ethics, Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine Learning, MIT Schwarzman College of Computing, Research, School of Engineering

Artificial intelligence is increasingly being used to help optimize decision-making in high-stakes settings. For instance, an autonomous system can identify a power distribution strategy that minimizes costs while keeping voltages stable.But while these AI-driven outputs may be technically optimal, are they fair? What if a low-cost power distribution strategy leaves disadvantaged neighborhoods more vulnerable to

Evaluating the ethics of autonomous systems Read More »

Preview tool helps makers visualize 3D-printed objects

3-D printing, Additive manufacturing, ai, AI (Artificial Intelligence), Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Machine Learning, Maker movement, Mechanical engineering, MIT Schwarzman College of Computing, Research, School of Engineering, Sustainability

Designers, makers, and others often use 3D printing to rapidly prototype a range of functional objects, from movie props to medical devices. Accurate print previews are essential so users know a fabricated object will perform as expected.But previews generated by most 3D-printing software focus on function rather than aesthetics. A printed object may end up

Preview tool helps makers visualize 3D-printed objects Read More »

MIT researchers use AI to uncover atomic defects in materials

ai, AI (Artificial Intelligence), Artificial Intelligence, Batteries, Computer modeling, Department of Energy (DoE), DMSE, Electrical engineering and computer science (EECS), Machine Learning, manufacturing, Materials science and engineering, Nanoscience and nanotechnology, National Science Foundation (NSF), Nuclear science and engineering, Research, School of Engineering, semiconductors, Solar

In biology, defects are generally bad. But in materials science, defects can be intentionally tuned to give materials useful new properties. Today, atomic-scale defects are carefully introduced during the manufacturing process of products like steel, semiconductors, and solar cells to help improve strength, control electrical conductivity, optimize performance, and more.But even as defects have become

MIT researchers use AI to uncover atomic defects in materials Read More »

Seeing sounds

ai, AI (Artificial Intelligence), Artificial Intelligence, Arts, Classes and programs, Computer science and technology, Electrical engineering and computer science (EECS), engineering, Games, Graduate, postdoctoral, Humanities, Mechanical engineering, Music, Music and theater arts, Music technology, Profile, School of Engineering, School of Humanities Arts and Social Sciences, Students, Undergraduate Research Opportunities Program (UROP)

Growing up in Mexico and Texas, Mariano Salcedo ’25 couldn’t readily indulge his passion for creating music. “There are no bands in Mexican public schools,” he says. While some families could pay for instruments and lessons, others, like Salcedo’s, were less fortunate.“I’ve always loved music,” he continues. “I was a listener.” Salcedo, the Alex Rigopulos (1992)

Seeing sounds Read More »

AI system learns to keep warehouse robot traffic running smoothly

ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Civil and environmental engineering, Computer science and technology, Electrical engineering and computer science (EECS), IDSS, Laboratory for Information and Decision Systems (LIDS), Logistics, Machine Learning, MIT Schwarzman College of Computing, Research, Robotics, School of Engineering, Supply chains

Inside a giant autonomous warehouse, hundreds of robots dart down aisles as they collect and distribute items to fulfill a steady stream of customer orders. In this busy environment, even small traffic jams or minor collisions can snowball into massive slowdowns.To avoid such an avalanche of inefficiencies, researchers from MIT and the tech firm Symbotic

AI system learns to keep warehouse robot traffic running smoothly Read More »

Augmenting citizen science with computer vision for fish monitoring

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), ai, AI (Artificial Intelligence), Animals, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, data, Ecology, Electrical engineering and computer science (EECS), Environment, Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT Sea Grant, National Science Foundation (NSF), Oceanography and ocean engineering, Research, School of Engineering, Undergraduate Research Opportunities Program (UROP), Video, Volunteering, outreach, public service, Water

Each spring, river herring populations migrate from Massachusetts coastal waters to begin their annual journey up rivers and streams to freshwater spawning habitat. River herring have faced severe population declines over the past several decades, and their migration is extensively monitored across the region, primarily through traditional visual counting and volunteer-based programs. Monitoring fish movement and understanding

Augmenting citizen science with computer vision for fish monitoring Read More »

A better method for identifying overconfident large language models

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

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular method involves submitting the same prompt multiple times to see if the model generates the same answer.But this method measures self-confidence, and even the most impressive LLM might be confidently

A better method for identifying overconfident large language models Read More »

Generative AI improves a wireless vision system that sees through obstructions

ai, AI (Artificial Intelligence), Artificial Intelligence, Computer science and technology, data, Electrical engineering and computer science (EECS), Electronics, Imaging, Machine Learning, Media Lab, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, Robotics, School of Architecture and Planning, School of Engineering, Sensors, Wireless

MIT researchers have spent more than a decade studying techniques that enable robots to find and manipulate hidden objects by “seeing” through obstacles. Their methods utilize surface-penetrating wireless signals that reflect off concealed items.Now, the researchers are leveraging generative artificial intelligence models to overcome a longstanding bottleneck that limited the precision of prior approaches. The

Generative AI improves a wireless vision system that sees through obstructions Read More »

MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact

Aeronautical and astronautical engineering, ai, AI (Artificial Intelligence), Algorithms, Artificial Intelligence, Careers, Collaboration, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical engineering and computer science (EECS), Industry, Laboratory for Information and Decision Systems (LIDS), Machine Learning, Mechanical engineering, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, Natural Language Processing, Research, Robotics, School of Engineering

The early years of faculty members’ careers are a formative and exciting time in which to establish a firm footing that helps determine the trajectory of researchers’ studies. This includes building a research team, which demands innovative ideas and direction, creative collaborators, and reliable resources. For a group of MIT faculty working with and on artificial

MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact Read More »