Sales of non-fungible tokens, or NFTs, reached $ 25 billion in 2021, indicating that this sector is one of the most sought-after markets for cryptocurrencies. In particular, art NFTs had such an impact last year that Christie’s reported sales of over $ 93 million in non-perishable tokens during the fourth annual Art + Technology Summit held in August last year.
While much of the crypto art scene is dominated by animation and memes, projects such as CryptoPunks and Bored Ape Yacht Club have been at the center. Although these projects are among the most successful to date, a new subgroup of NFTs based on advanced technology and human imagination is emerging.
AI-made NFTs are becoming a new art genre
These non-fungible tokens, known as “AI-created NFTs,” are becoming increasingly popular in the art community, as well as those interested in new technologies such as artificial intelligence, blockchain and metaverse. Generative Adversarial Networks or GANs can typically be used to create AI-generated NFTs. These are algorithms that computers use to use data to train models to create artificial machine-generated images.
Claire Silver, an AI collaborating artist, told the Cointelegraph that AI-generated NFT art is a relatively new genre, noting that the basic principle is that art is created along with an appearance of AI as GAN:
“There are code-heavy alternatives and completely code-free tools that everyone can work with. I use the latter in my work. Being able to work with AI to bring your ideas to life is an experience like no other, it increases creativity in a way that feels like freedom, a kind of game you have not experienced since childhood. ”
Silver explained that to create AI-generated NFTs, he uses a text-to-art conversion tool called “Eponym”. Developed by AI-powered art company Art AI, Eponym allows users to create artwork based on the text they want and then post the creations directly to the largest NFT marketplace, OpenSea.
“Cassandra Ex Machina” Source: Claire Silver
Art AI co-founder Eyal Fisher told Cointelegraph that Eponym allows any statement to be turned into a unique piece of NFT art that will forever be engraved on the Ethereum blockchain as a visual representation.
Fisher explained that Eponym is built on custom drawing algorithms that allow people to create artwork by interacting with a computer. Eponym is a joint NFT project. Users can access it by logging on to a website and typing a sentence or word in the text field. AI then creates an image based on the specified text. “Fisher added that each text message can only be generated once.” There is only one name, Bitcoin, “he said.
Image “$ btc” by Eponym Source: Eponym
While generative artificial intelligence is a fairly new concept, Fisher shared that the first Eponym project was sold out overnight at OpenSea, making it one of the largest collaborative art projects created by 3,500 different artists. This is an experiment in the decentralization of art. The people who own the eponyms are the creators of this art, and they want to harmonize it. ”
While Eponym allows users to create their own artistic NFTs, Metascapes is another project developed by three photographers who want to combine human expression with computer algorithms. Ryan Newborn, one of the Metascapes photographers, told Cointelegraph that the project consists of 3333 rare AI-generated NFTs based on images taken around the world. Like Eponym, Metascape uses AI algorithms to create nature-inspired NFTs. According to Newborn, the first group Metascapes is scheduled to be launched at the end of this month or the beginning of February.
Ice Journey Source: Metascapes
Metascape’s artificial intelligence team, called Versus Labs, explained that the illustrations in each set are generated from training data for photorealistic image recognition:
“We have pictures and photo tags called ‘training data’. When it’s time to create the output model, we put a label that tells the model which pictures to place. For example, ice caves and volcanoes were two categories that photographers used in the past, but they were not. the majority of the input, so we wanted to make sure that the output contained examples from ice caves and volcanoes. ”
