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Welcome to Open Mind Common Sense! Computers don't currently know the basic things about the world that we consider "common sense." Here, you can help build a database of such knowledge in simple English sentences. The computer will analyze these sentences to connect concepts and draw new conclusions from the things you teach it. This project, Open Mind Common Sense, enables computers to learn general knowledge from ordinary people over the Web.
Open Mind Common Sense : Welcome
MIT Department of Earth, Atmospheric and Planetary Sciences (EAPS)
In the News: Adjusting the Rock Clock: Postdoc Noah McLean and scientists at the British Geological Survey have redefined a fundamental parameter used to calibrate Earth's history. In their recent Science paper, they report variations in the uranium isotopic composition of minerals used to date major geological events. Read MoreConceptNet | Common Sense Computing Initiative
ConceptNet aims to give computers access to common-sense knowledge , the kind of information that ordinary people know but usually leave unstated. The data in ConceptNet is being collected from ordinary people who contributed it on sites like Open Mind Common Sense . ConceptNet represents this data in the form of a semantic network, and makes it available to be used in natural language processing and intelligent user interfaces. ConceptNet is an open source project, with a Python implementation and a REST API that anyone can use to add computational common sense to their own project. A great tool to help you use ConceptNet in your software is Divisi . Some of the nodes and links in ConceptNet.Common Sense Computing Initiative | at the MIT Media Lab
SIMILE Project
Free Online Course Materials | MIT OpenCourseWare
An inspiring trip to Haiti and publishing educational materials that matter: read about it in the newest letter from executive director Cecilia d'Oliveira.The mission of MIT is to advance knowledge and educate students in science, technology, and other areas of scholarship that will best serve the nation and the world in the 21st century. The Institute is committed to generating, disseminating, and preserving knowledge, and to working with others to bring this knowledge to bear on the world's great challenges. MIT is dedicated to providing its students with an education that combines rigorous academic study and the excitement of discovery with the support and intellectual stimulation of a diverse campus community.
Chaîne de MIT - YouTube
Pranav Mistry (b. 1981 in Palanpur , India ) is one of the inventors of SixthSense . [ 1 ] He is a research assistant and a PhD candidate at MIT Media Lab . Before joining MIT he worked as a UX Researcher with Microsoft. He received Master in Media Arts and Sciences from MIT and Master of Design from IIT Bombay.
Pranav Mistry - Wikipedia, the free encyclopedia
Creating an App Inventor app begins in your browser, where you design how the app will look. Then, like fitting together puzzle pieces, you set your app's behavior. All the while, through a live connection between your computer and your phone, your app appears on your phone. You can build many different types of apps with App Inventor. Often people begin by building games like MoleMash or games that let you draw funny pictures on your friend's faces.
MIT App Inventor
Out of (Line of) Sight, But Not Out of View: The Camera Culture group at the Media Lab has created CORNAR: Looking around Corners with Femtophotography. With CORNAR, femtosecond imaging technology provides a way to see things beyond the line of sight–allowing us to see what's around the corner.
MIT Media Lab
Deb Roy is a tenured member of the MIT faculty and directs the Cognitive Machines group at the MIT Media Lab. Roy is currently on leave from MIT and serves as CEO of Bluefin Labs , a venture-backed technology company that he cofounded in 2008. A native of Canada, Roy received his bachelor of computer engineering from the University of Waterloo in 1992 and his PhD in cognitive science from MIT in 1999.
Deb Roy - MIT Media Laboratory
Machine Perception and Learning of Complex Social Systems Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.

