Shared publicly  - 
+Google, consistently making golden-age sci-fi reality, one bit at a time.
I've been working on training systems for very large neural networks recently.  One cool result we've found is that a large network trained with totally unlabeled data can automatically discover high-level concepts like human faces, cats, etc. (cats because we trained on still images from a large collection of YouTube videos).

+John Markoff wrote up a very nice article in the New York Times today that describes how we've been applying these systems to various problems in computer vision.

+Quoc Le, +Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, +Greg Corrado, +Andrew Ng, and I wrote a paper to appear at this week's ICML conference, which has a bit more technical detail about the system.

The ICML paper is here:

The NY Times article is here:
Building High-level Features Using Large Scale Unsupervised Learning Quoc V. Le, Marc'Aurelio Ranzato, Rajat Monga, Matthieu Devin, Kai Chen, Greg S. Corrado, Jeffrey Dean, and Andrew Y. Ng. Cat and f...
Add a comment...