Hey Alexa! Sorry I fooled you ...
MIT’s new system TextFooler can trick the types of natural-language-processing systems that Google uses to help power its search results, including audio for Google Home.
MIT’s new system TextFooler can trick the types of natural-language-processing systems that Google uses to help power its search results, including audio for Google Home.
Routing scheme boosts efficiency in networks that help speed up blockchain transactions.
Doctoral candidate Natalie Lao wants to show that anyone can learn to use AI to make a better world.
The 2019-20 School of Engineering MathWorks Fellows are using MATLAB and Simulink to advance discovery and innovation across disciplines.
Qubits made from strontium and calcium ions can be precisely controlled by technology that already exists.
Model tags road features based on satellite images, to improve GPS navigation in places with limited map data.
A new method determines whether circuits are accurately executing complex operations that classical computers can’t tackle.
Associate Professor Yury Polyanskiy is working to keep data flowing as the “internet of things” becomes a reality.
Models that map these relationships based on patient data require fine-tuning for certain conditions, study shows.
Using mathematical theory, Virginia Williams coaxes algorithms to run faster or proves they’ve hit their maximum speed.
Machine-learning system should enable developers to improve computing efficiency in a range of applications.
As natural language processing techniques improve, suggestions are getting speedier and more relevant.
Using limited data, this automated system predicts a company’s quarterly sales.
Weekend robotics workshops help middle and high school girls dispel “computing phobia.”
Objects are posed in varied positions and shot at odd angles to spur new AI techniques.