Machine learning and deep learning are increasingly disrupting all sectors of society, making it possible to improve artificial intelligence, halt the spread of malware, among many other benefits. However, scientists are not the only ones interested in it. As part of a series of blog posts, CMF Trends met with Google engineer Damien Henry during the Google I/O 2016 developers conference. Damien Henry leads the Cultural Institute Experiment Team (CILEx), part of the Google Cultural Institute. This team uses modern tools -- including machine learning -- for artistic purposes.

In artnet's predictions for 2017, I wrote that it would be the year Artificial Intelligence would finally crack the problem of curating. That was meant as a joke--but it turns out that I was already behind the times. The whiz kids at Google's non-profit cultural arm, Google Cultural Institute, have spent the year trying to imagine just that. Head to the "Experiments" section of the Cultural Institute website and you will find a catalogue of how they have been attempting to apply "machine learning" to the question of organizing artworks. Perhaps the experiment that best showcases their particular brand of cultural gimcrackery is called "X Degrees of Separation."

We're happy to announce Magenta, a project from the Google Brain team that asks: Can we use machine learning to create compelling art and music? Soon we'll begin accepting code contributions from the community at large. If you'd like to keep up on Magenta as it grows, you can follow us on our GitHub and join our discussion group. First, it's a research project to advance the state of the art in machine intelligence for music and art generation. Machine learning has already been used extensively to understand content, as in speech recognition or translation.

We're happy to announce Magenta, a project from the Google Brain team that asks: Can we use machine learning to create compelling art and music? Soon we'll begin accepting code contributions from the community at large. If you'd like to keep up on Magenta as it grows, you can follow us on our GitHub and join our discussion group. First, it's a research project to advance the state of the art in machine intelligence for music and art generation. Machine learning has already been used extensively to understand content, as in speech recognition or translation.

Can a machine be creative? Google thinks so, and it has an entire team dedicated to teaching machines how to view the world a little more like us emotional humans. Think about computers as if they were children and it's simple to understand how coders can teach them to learn. Artificial intelligence is, at the beginning, very basic and simple. Human moderators instruct computers, showing them how to think and thus teach themselves.

Can a machine be creative? Google thinks so, and it has an entire team dedicated to teaching machines how to view the world a little more like us emotional humans. Think about computers as if they were children and it's simple to understand how coders can teach them to learn. Artificial intelligence is, at the beginning, very basic and simple. Human moderators instruct computers, showing them how to think and thus teach themselves.

Can a machine be creative? Google thinks so, and it has an entire team dedicated to teaching machines how to view the world a little more like us emotional humans. Think about computers as if they were children and it's simple to understand how coders can teach them to learn. Artificial intelligence is, at the beginning, very basic and simple. Human moderators instruct computers, showing them how to think and thus teach themselves.