Exact symbolic artificial intelligence for faster, better assessment of AI fairness
Probabilistic programming language allows for fast, error-free answers to hard AI problems, including fairness.
Keylime security software is deployed to IBM cloud
Originally developed at MIT Lincoln Laboratory, the technology allows organizations to ensure the security of sensitive data stored in the cloud.
Contact-aware robot design
A novel method to represent robotic manipulators helps optimize complex and organic shapes for future machines.
US Air Force pilots get an artificial intelligence assist with scheduling aircrews
An optimization tool from the Department of Air Force–MIT AI Accelerator is transforming the laborious process of staffing C-17 cargo flights.
The power of two
Graduate student Ellen Zhong helped biologists and mathematicians reach across departmental lines to address a longstanding problem in electron microscopy.
The new wave of robotic automation
Peter Howard SM ’84 is the CEO of Realtime Robotics, a startup transforming autonomous robot motion planning to enable seamless, affordable human-robot collaboration.
Training robots to manipulate soft and deformable objects
A virtual environment embedded with knowledge of the physical world speeds up problem-solving.
From gas to solar, bringing meaningful change to Nigeria’s energy systems
Chemical engineering senior Awele Uwagwu works to accelerate the adoption of solar energy in Nigeria.
Crowdsourcing data on road quality and excess fuel consumption
MIT researchers are using smartphones to gather roadway information previously inaccessible to many departments of transportation.
New system cleans messy data tables automatically
With just 50 lines of code, the program spots and fixes likely errors.
Turning technology against human traffickers
Lincoln Laboratory connects counter–human trafficking community in pursuit of technology to help investigate cases.
Q&A: Vivienne Sze on crossing the hardware-software divide for efficient artificial intelligence
Her research focuses on more-efficient deep neural networks to process video, and more-efficient hardware to run applications.
Innovative design thinking for a fast-changing world
Blade Kotelly is a senior lecturer on design thinking and innovation, bringing expertise to the world's top brands to better innovate in complex product and service environments.
Researchers develop speedier network analysis for a range of computer hardware
The advance could boost recommendation algorithms and internet search.
Center to advance predictive simulation research established at MIT Schwarzman College of Computing
MIT is among nine universities selected as part of a program sponsored by the DoE to support science-based modeling and simulation and exascale computing technologies.