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By CNBCTV18.com  IST (Published)

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NFTs have become the second most used utility of blockchain technology after cryptocurrencies. They are also seen as a store of wealth and the ultimate way for artists to put forth their work in a profitable manner. The drastic evolution of this asset class has also resulted in the creation of different types of NFTs, from static to dynamic and now generative NFTs. In this article, we learn what generative NFTs are and how they work.

NFTs have broken into pop culture as nothing else has in the past decade. Today, several celebrities, including Justin Bieber, Neymar Jr, Jimmy Fallon, etc. own one or more NFTs. There’s also a TV series being developed around an NFT character. Not to mention, NFTs were also featured at this year’s Video and Music Awards (VMAs). Even some of the biggest brands have begun to jump onto the NFT bandwagon.

As such, NFTs have become the second most used utility of blockchain technology after cryptocurrencies. They are also seen as a store of wealth and the ultimate way for artists to put forth their work in a profitable manner. The drastic evolution of this asset class has also resulted in the creation of different types of NFTs, from static to dynamic and now generative NFTs. In this article, we learn what generative NFTs are and how they work.

What are generative NFTs?

Generative NFTs are a collaboration between man and machine. Artists can compile a basic bouquet of colours, patterns, backgrounds, characters and images upon which they wish to base their NFT collection. They can then feed these elements into a computer code which begins generating artworks using random permutations and combinations of the provided elements.

Generative NFTs revolve around three core factors: randomness, geometry and algorithms. Randomness ensures that even the artist cannot predict the outcome of a generative artwork. Perfect geometry, which computers are known for, helps create visually stunning artworks. And the algorithm ensures that minimal human intervention is needed.

How is it done?

Generally, it starts with the artist adding a set of images and rules to a code. The algorithm will take all the provided images, patterns, backgrounds, etc., and create random artworks based on the rules specified in the code. The rules can govern the usage of colours and patterns, the number of iterations between each artwork and the randomness quotient.

If you don’t have any coding knowledge, you can use an AI-based digital art creator like starryai or HotPot AI. These platforms will cover all the coding and allow you to create generative NFTs in a flash. Once you have received the image, you can mint it as an NFT, which is then stored permanently on the blockchain.

Note that the AI generators usually have different paid plans and take about 30 minutes to create your art. The free creators either do not transfer the copyright to you (so you cannot create an NFT of the artwork) or have a large watermark printed on them, blocking you from free usage.

Examples of generative NFTs

Here’s a quick round-up of some of the most prolific generative NFT artworks seen so far.

Autoglyphs: Launched in 2019 by LarvaLabs (the creators of the popular CryptoKitties NFT collection), Autoglyphs is considered the first ever generative NFT art project. When they were initially released, the NFTs could be minted for as little as 0.2 ETH each. However, due to their limited supply (just 512 artworks), they have quickly risen to popularity and now demand a floor price of 189 ETH, roughly $230,000.

Fidenza: This colourful collection of 999 NFTs is another prominent name in the generative NFT scene. It is the brainchild of Tyler Hobbs, a computer engineer who quit his job to fulfil his dream of becoming an artist. The collection is named after a small town in Italy and was sold out in 25 minutes at 0.17 ETH per piece. Hobbs netted $400,000 in the initial sale and over $4 million in commission through secondary sales.

Ringers: This is a series of 1,000 generative NFTs created by Canadian artist and coder Dmitri Cherniak. The collection draws inspiration from a string being looped around of set of pegs, and each artwork is created through Cherniak’s special p5js script. The rules of the script govern peg count, size, layout schemes, orientation, and colours to create mesmerizing outcomes upon minting. The collection sold out within 20 minutes of its release for 0.1 ETH each. Since then, it has racked up close to $1 million in secondary sales.

Conclusion

Computer-generated art was never considered valuable or given much importance. However, with the right input from talented artists, these machine and AI-based artworks can be a spectacle to behold. Therefore, despite being a relatively novel concept, these NFT artworks have already sold for millions of dollars and continue to see bullish demand.