# Topics > Artificial neural networks > Machine learning, deep learning >  A.I. Experiments, exploring machine learning by playing with pictures, language, music, code, and more, Google Inc., Mountain View, California, USA

## Airicist

Developer - Google Inc.

Home page - aiexperiments.withgoogle.com

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## Airicist

What does A.I. have to do with this selfie?

Published on Oct 26, 2016




> Recently, you may have noticed people sharing stylized photos and videos that resemble famous paintings, like "Starry Night" by Van Gogh and "The Scream" by Munch. But how do the apps that make these images work? How can the style of a painting be transferred to a selfie or a photo of your dog? Turns out, a whole lot of A.I. using machine learning and deep neural networks. In this video, we break down the basics of how style transfer works, and demo some recent style transfer experiments created by research scientists at Google.


Playlist "Nat & Lo: All Episodes"

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## Airicist

Machine learning: making sense of a messy world

Published on Nov 3, 2015




> The world is filled with things that most of us are able to understand and react to without much thought… a stop sign partially covered by snow is still a stop sign… a chair that’s five times bigger than usual, is still a place to sit. But for computers, the world is often messy and complicated. Google engineers and researchers discuss how machine learning is beginning to make computers, and many of the things we use them for (maps, search, recommending videos, translations), better. 
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> Google engineers and researcher (in order of appearance): Blaise Aguera Y Arcas, Greg Corrado, John Giannandrea, Peter Norvig, Jeff Dean, Geoffrey Hinton, Anna Patterson.

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## Airicist

A.I. Experiments: Making it easier for anyone to explore A.I.

Published on Nov 15, 2016




> With all of the exciting A.I. stuff happening, there are lots of people eager to start tinkering with machine learning technology. That's why we've created A.I. Experiments, a site that showcases simple experiments that let anyone play with this technology hands-on, and resources for creating your own experiments.
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> Various visualizations featured in video made by Gene Kogan. Additional footage by Sarah Riazati.

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