Artificial Intelligence developments: the year in review

TechCrunch, a popular site dedicated to technology news, has published a list of the the top Artificial Intelligence news of 2016.

2016 seems indeed to have been the year Artificial Intelligence (AI) left the confinement of university labs to come into public view.

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Several of the news selected by TechCrunch, were also covered in this blog.

In March a Go playing program, developed by Google’s DeepMind, AlphaGo, defeated 18-time world champion Lee Sedol (reference in the TechCrunch review).

Digital Art, where deep learning algorithms learn to paint in the style of a particular artist, was also the topic of one post (reference in the TechCrunch review).

In May, Digital Minds posted Moore’s law is dead, long live Moore´s law, describing how Google’s new chip can be used to run deep learning algorithms using Google’s TensorFlow (related article in the TechCrunch review).

TechCrunch has identified a number of other relevant developments that make for an interesting reading, including the Facebook-Amazon-Google-IBM-Microsoft mega partnership on AI, the Facebook strategy on AI and the news about the language invented by Google’s translation tool.

Will the AI wave gain momentum in 2017, as predicted by this article? I think the chances are good, but only the future will tell.

Can Prisma and DeepArt make everyone an artist?

The popularity of Prisma, one of the hot summer apps (together with Pokemon Go), has caught everyone by surprise, including its creators.

Prisma uses deep learning algorithms to derive image processing methods that change your pictures in accordance with the style of a given artist. Other sites, like DeepArt and DeepDream, apply these methods based on machine learning techniques, such as the one described in this article, to process photos that you upload.

The following drawing of The Thinker was obtained applying Prisma to one of my travel pictures.

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The following “painting” was obtained from one image of the tall ships in Lisbon, using DeepArt.

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Applying the methods takes significant computer time, and is done by Prisma remote servers. These servers have, for a while, been unable to fully cope with the demand. Other sites, like DeepArt, also take significant time to process your request.

The results are, in many cases, surprising, obscuring the line between artistic merit and computerized image processing. Recently, Google raised a significant amount of money selling computer generated art.

For more examples of computer generated art, using Prisma and DeepArt, take a look at my deep art flickr album.

Google raised $84,000 auctioning computer generated art

Last February, Google auctioned a number of computer generated paintings, raising $84,000 for the Gray Area Foundation for the Arts, a San Francisco nonprofit institution devoted to the convergence of art and technology.

The auction took place during a two day event, which also included a symposium about the technology used to generate the paintings.

 

but-its-when-an-image-goes-through-those-final-layers-where-the-image-output-gets-really-weird-this-layer-will-look-for-complex-things-like-an-entire-buildingThese paintings were generated using a technology dubbed inceptionism, which uses internal representations of neural networks trained using deep learning to derive abstract images, with styles that remind us of different visual art styles. The painting are the results of a project dubbed DeepDream, which can be used by anyone to make their own artworks.

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This kind of artwork is probably going to become more common, as more people get interested and more computers “decide” to become artists….

Both the University of London and NYU are now offering courses on computer generated art.