AI makes art

Botnik Studios is using deep learning to create art. For example, they used deep learning to imitate a Coachella poster. Indeed, it was trained a recurrent neural network on thousands of band names. 

Botnik trained a predictive model to generate a top 10 trending hashtags list. This predictive-keyboards model was used to write a Scrubs episode and a passage of the Trump tell-all Fire and Fury.

It was trained a deep learning model to draw based on photo captions that Microsoft researchers shared last week. Botnik is using deep learning to create art.

Prisma, Facebook, Google, and Algorithmia are using Style transfer to recreate your photos with the style of Picasso, Van Gogh, or Monet. So, it’s not like deep learning is stealing the job of creative artists. But, this algorithm can imitate their style to create something new.

For example, a tech-art incubator at Gray Area Foundation displayed art generated by Google’s DeepDream. So, it was used deep learning to generate imagery. The room was full of art generated by deep learning algorithms.

Deep learning is used to imitate styles, but there are some artist-technologists that are using this technology for something else than increasing efficiency.

In art, the most important is to be original. That’s the main point of art. The artists must find their own voice and express it. So, other people feel a connection with their art. Artificial intelligence is used to recreate art or copy the artists’ style, but artist-technologists must use deep learning to create art that other people feel inspired and excited.  

Artificial intelligence tools will be improved and new AI tools will emerge that might be able to imitate human creativity, but using deep learning for art doesn’t mean the end of creativity.

Using deep learning to create something artistic such as painting, a joke, or a song is just a dream. So, using technology to create something that needs imagination is something that we all want to see.  

In fact, machine-learning applications such as IBM’s Deep Blue won a chess match with a human player. Another example is that AlphaGo (AI tool) won a Go game with Lee Sedol.

Deep learning and humans can produce unique pieces of art, but deep learning can’t replace human creativity and ingenuity. Indeed, deep learning can be used to multiply human ingenuity by learning their artistic styles.

Artificial intelligence in the art can augment art, but it cannot replace human creativity. So, it helps humans to discover new forms of expression.

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