This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.
This CoR aims to develop AI technology that synthesizes symbolic reasoning, probabilistic reasoning for dealing with uncertainty in the world, and statistical methods for extracting and exploiting regularities in the world, into an integrated picture of intelligence that is informed by computational insights and by cognitive science.
MIT App Inventor is an intuitive, visual programming environment that allows everyone – even children – to build fully functional apps for smartphones and tablets.
We focus on understanding the problem-solving strategies used by scientists and engineers, with the goals of automating parts of the process and formalizing educational methods.
The Weiss Lab seeks to create integrated biological systems capable of autonomously performing useful tasks, and to elucidate the design principles underlying complex phenotypes.
We aim to develop a systematic framework for robots to build models of the world and to use these to make effective and safe choices of actions to take in complex scenarios.
The robot garden provides an aesthetically pleasing educational platform that can visualize computer science concepts and encourage young students to pursue programming and robotics.
The Robot Compiler allows non-engineering users to rapidly fabricate customized robots, facilitating the proliferation of robots in everyday life. It thereby marks an important step towards the realization of personal robots that have captured imaginations for decades.
By crunching 130 million mouse-clicks, two CSAIL researchers have developed a machine-learning model that can predict with surprising accuracy whether or not a MOOC student will drop out of a given course.
