Algorithms
Algorithms

Algorithms

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Faculty Food machine learning Research School of Engineering Sustainability

Streamlining data collection for improved salmon population management

Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.

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

3 Questions: Modeling adversarial intelligence to exploit AI’s security vulnerabilities

MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.

Algorithms Artificial Intelligence Computer science and technology Games machine learning Media Lab Research Robotics School of Architecture and Planning

New training approach could help AI agents perform better in uncertain conditions

Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Automation Autonomous vehicles computer-vision Drones Faculty Laboratory for Information and Decision Systems (LIDS) MIT Schwarzman College of Computing Profile Robotics School of Engineering Software

Expanding robot perception

Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.

Algorithms Artificial Intelligence Cleaner industry Climate Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data DMSE Electrical engineering and computer science (EECS) Emissions Energy Environment Human-computer interaction machine learning MIT Schwarzman College of Computing School of Engineering Sustainability Sustainable computing Water

Explained: Generative AI’s environmental impact

Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Faculty Health Care Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT Sloan School of Management Profile School of Engineering social media Technology and society

Algorithms and AI for a better world

Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.

Algorithms Artificial Intelligence Computer science and technology Data Electrical engineering and computer science (EECS) Faculty Health Care Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT Sloan School of Management Profile School of Engineering social media Technology and society

Algorithms and AI for a better world

Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.

Algorithms Artificial Intelligence Brain and cognitive sciences Center for Brains Minds and Machines Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction machine learning MIT Schwarzman College of Computing Music Research School of Engineering School of Science

Teaching AI to communicate sounds like humans do

Inspired by the mechanics of the human vocal tract, a new AI model can produce and understand vocal imitations of everyday sounds. The method could help build new sonic interfaces for entertainment and education.

Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Ecologists find computer vision models’ blind spots in retrieving wildlife images

Biodiversity researchers tested vision systems on how well they could retrieve relevant nature images. More advanced models performed well on simple queries but struggled with more research-specific prompts.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Natural language processing Quest for Intelligence Research Robotics School of Engineering

Teaching a robot its limits, to complete open-ended tasks safely

The “PRoC3S” method helps an LLM create a viable action plan by testing each step in a simulation. This strategy could eventually aid in-home robots to complete more ambiguous chore requests.