Blockchain artificial intelligence lab Fetch.ai has launched a new NFT marketplace for AI-generated art, giving users the ability to create digital collectibles in a collaborative setting through car learning engineering science.

The new platform, dubbed Colearn Paint, allows groups of creators to automatically generate and collectively own NFTs designed by a machine learning algorithm. The platform is geared towards "abstract compositions," co-ordinate to Humayun Sheikh, CEO of Fetch.ai, who cited "collective learning" as a major trend for the future.

Commonage learning is a concept within artificial intelligence that describes the awarding of deep learning algorithms to information and privacy.

Users of Colearn Paint will be taken through a iii-stride process for creating randomly generated NFTs. The first step entails bidding through a dutch auction to participate in the commonage learning process. The winning bidders will input a "randomness blueprint" and select art from the prearranged AI-generated options. The concluding footstep is the creation and sale of the NFT, which will allow users to distribute the profits among themselves.

Related: Fetch.ai (FET) hits a 2-year high after DeFi integration and Bosch partnership

NFTs have emerged as ane of the most popular blockchain use cases, with investors and venture funds peachy to back this and then-called future of creativity. Several loftier-profile NFT marketplaces take launched this year, each with its ain focus and desired utility. The nascent industry has truly striking its footstep in 2022, with NFT sales topping $2.v billion in the first half of the year.

Every bit Cointelegraph reported, credit bill of fare behemothic Visa recently made a splash in the NFT infinite by purchasing a CryptoPunk for $150,000. In June, a CryptoPunk NFT sold for $11.8 meg on Sotheby's auction house. Fetch.ai believes that AI-generated art options could steer the management of the NFT market past giving users a more streamlined process for creating and monetizing digital abstractions.

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