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The Machine Learning Powering Generative Art NFTs

1 min read Original Link

Artificial intelligence (AI) in the non-fungible token (NFT) space is becoming increasingly relevant. Generative art (that is, art that has been created by an autonomous system) has quickly emerged into one of the main categories of the NFT market, driving innovative projects and astonishing collections. From the works of AI art legends such as Refik Anadol or Sofia Crespo to Tyler Hobbs’s new QQL project, NFTs have become one of the main vehicles to access AI-powered art.

Generative art has been one of the quintessential machine-learning use cases, but only recently has the space achieved mainstream prominence. The leap has been mostly powered by computational gains and a new generation of techniques that can help models learn without requiring a lot of labeled datasets, which are incredibly limited and expensive to build. Even though the gap between the generative art community and AI research has been closing in the last few years, many of the new generative art techniques still haven’t been widely adopted by prominent artists, as it takes a while to experiment with these new methods.

(by Jesus Rodriguez)

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