What Does a Self-Evident Truth Look Like?

Or how about a feeling, obsession, or stochastic variable? How can those concepts be visually represented? Now you know thanks to the 800 Million Tiny Images project from the Computer Science and Artificial Intelligence Laboratory (CSAIL).

The research offers a mosaic visualization of all the nouns in the English language arranged by semantic meaning. Each of the mosaic's tiles is an arithmetic average of 140 images relating to one of 53,464 nouns, revealing the dominant visual characteristics of each word. Researchers Antonio Torralba, associate professor of electrical engineering and computer science (EECS); William T. Freeman PhD ’92, professor of EECS; and Rob Fergus, previously a CSAIL post-doc and now an assistant professor at NYU used a total of 7,527,697 images from Google's image search and other engines.

Click anywhere in the visual dictionary to find the word corresponding to that semantic location, the average image, and the first 16 images returned by the online image search tools.

And you may be happy to know that MIT is more colorful than that other school along the Charles River. As if there was ever any doubt.