Art in the digital world

• Gans

• Discourse

• Blockchain

• NFT examples

• Discourse

Conclusion

In its current state, AI lacks the consciousness to go beyond what it’s been trained to do; it must be a collaborative effort between human and machine. In art, AI acts as a medium for artists to create — data replaces pigments and algorithms replace brushes.

One of the first AI-generated pieces to shake the art world was Obvious’s

Portrait of Edmond Belamy 

which sold at Christie’s auction house for $432,500. French research group Obvious created the portrait by using Apple’s director of machine learning

’s GAN technology and a database containing 14 thousand portraits from the 15th to 20th century.

Generative Adversarial Networks (GAN) are a type of gradient descent which uses two

that compete against each other to create accurate predictions. Adversarial training trains machine learning systems by focusing on their weaknesses in order for machines to learn how to improve upon themselves. GANs use two neural networks: generator and discriminator. Generator trains on image data and creates a new one. Discriminator tries to detect if an image is fake (created by the generator) or real (image from the training set). The generator’s goal is to trick the discriminator as much as possible. The goal of the discriminator is to detect as many fake images as possible. Over time, the generator learns how to create such realistic images that the discriminator can’t tell the difference.

In the case of the

Portrait of Edmond Belamy, 

the generator created portraits which the disminator eventually couldn’t distinguish from the portraits of 14th to 20th century art. The result was a 12 piece series called

Le Famille De Belamy

. Despite the piece’s success at auction, many critics were left to question the true authorship of this piece: was it Robbie Barrat, the creator of the algorithm that Obvious based there’s off of? Or was it a collaborative effort of the thousands of artists who unknowingly made up the dataset the algorithm ran on? While art critics may debate over these questions for years to come, the success of the Portrait of Edmond Belamy shows how AI can be used as another tool in which art can be created.

The rise of cryptocurrency has brought about one of the hottest topics in art: Non fungible tokens (NFTs). Commodities can be broken down into two categories: fungible and non-fungible. Non-fungible objects are one-of-a-kind and hold a greater monetary value than fungible items. For example, the thousands of basketballs in stores are fungible — the consumer just wants a basketball. A basketball that was used to score the winning point in an NBA final is non-fungible as only one exists.

NFT’s exist on the Ethereum blockchain. The blockchain is a database that acts as a ledger for storing cryptocurrency transactions. As new information comes into the blockchain, millions of computer systems will work to add a new block to the chain of previous block transactions. All transactions on the blockchain are publicly recorded and permanently stored. Ethereum is a cryptocurrency that supports NFTs by giving them a unique signature that makes them non-fungible from other types of cryptocurrency. NFTs made it so artists and creators on the internet could make their public images a scarce commodity.

In the last few years everyone from celebrities, artists, and brands have been creating NFTs and found lucrative success. In the world of sports memorabilia, NBA Top Shot sells game highlights as NFTs. As of February 2021, they’ve netted over $230 million collectively. The NFT marketplace has brought together both artists and brands who are commodifying their work in unique tokens to be sold. The single highest grossing sale of an NFT came about in March 2021 when artist Beeple sold his piece 

Everydays 

for $69 million. The piece was a compilation of the first 5,000 days of his work on one unique token.

The rise of NFTs has spurred other ventures that merge art, technology, and gaming. Zed Run is a tech company which created NFT horses. Unlike traditional NFTs which are videos, GIFs, and photos, Zed Run’s horses have a unique set of digital DNA leading the owners to call them “breathing NFTs”. Owners can breed NFT horses together to create a new horse that shares the favorable DNA on the parents genetics and bloodlines. Zed Runs adds an extra element to NFTs by letting owners race their horses. Winners are chosen by running 10 thousand simulations within an algorithm and randomly selecting one. Races are influenced by the DNA and past performances of the horses. While still a new idea, Zed Run has been able to regularly sell it’s NFT horses for $15,000 with the highest sale for a horse going for $125,000.

All of the buzz and innovation surrounding NFTs hasn’t come without criticism. The computers used to run the blockchain, and thus, NFTs, take up a substantial amount of energy. Some worry that the rise in popularity of NFTs will only increase cryptocurrency’s carbon footprint. Others have questioned the value of NFT files as exact copies of images and videos sold are easily available online for anyone too view. Whereas a painting can be displayed in one’s house or a museum, an NFT only exists online and can be printed and repurposed by the owner or casual viewer. Despite the criticism, many digital artists are pleased with the rise in NFTs as it gives their digital work monetary value and prestige within the art world.

Throughout time, art has never remained stagnant. Computers have changed every aspect of how we live our lives, art hasn’t been spared from this change. From AI being able to create new pieces in tandem with humans, or the blockchain changing the way art is bought, sold, and consumed, there are seemingly endless possibilities to ways that artists adapt with technology.