Since their meteoric rise to fame in 2017, NFTs — an acronym that stands for non-fungible tokens — have become the staple of the crypto ecosystem, onboarding millions of artists, collectors, and flippers to the Web3 space. Love them or hate them, the ridiculously expensive kitsch monkey JPEGs are likely here to stay: after all, the simple idea of recording media on the blockchain gave birth to the multi-billion ecosystem of marketplaces, NFT development labs, NFT-powered games, gaming studios, and DAOs, which became intertwined with the broader crypto market to the point of being inseparable.
Although the hype in the NFT market has lost some of its steam since its peak in 2021, the space continues to evolve, this time spawning the love child of the two most buzzy technologies of today, namely blockchain and Artificial Intelligence. The AI NFTs open the door to new forms of artistic expression, lowering the barrier to entry for more aspiring creators. So, what exactly is this new brand of NFTs, and how can you tap into this novelty?
Generative AI NFTs explained
As one can easily infer from the title, AI NFTs are non-fungible tokens that somehow incorporate Artificial Intelligence to create any forms of art, be it visual, musical, or literary. AI technology, whose theoretical foundations have been laid as early as in the 1940s by English mathematician Alan Turing, has undergone immense progress over the last couple of years, mostly due to the increase in computational power available for training models and the advance in deep learning algorithms that underlie the most prominent image generators and language models today.
This sophisticated and mathematically heavy technology has already changed many aspects of our daily life, sometimes even without us noticing. For instance, every time you input some text into Google Translate, there’s a powerful neural network running under the hood. And whenever you use online maps to navigate busy traffic, choose the next movie to watch on Netflix, or ask the voice assistants about the best local restaurants, the AI is involved as well.
Coming to NFTs, AI found its use in the digital art industry, producing some of the most iconic collections. The AI in question — Generative Adversarial Network, or simply GAN — is trained on terabytes of the visual data to recognize patterns in images and use them to generate the unique artworks. To create the new images, this machine learning algorithm relies on text input from the user, the so-called prompts, which usually include specific descriptions, shapes, textures, colors, and styles. The output produced by the model can be additionally fine-tuned and edited to get rid of minor glitches and add some fine details.
When the artwork is ready, it can be minted on the blockchain, with Ethereum, Solana, and Polygon being the top picks for NFT developers due to their wide user bases and supporting infrastructure, such as marketplaces, aggregators, and NFT-powered games.
How are Generative AI NFTs created?
Now that we know about how the fusion of AI and NFTs produced one of the most important trends in digital art, let’s examine in more detail how such artworks are created.
GAN coding and training: obviously, the very first step in creating an AI NFT from scratch would be to code the underlying machine learning algorithm and train it on the dataset large enough for the model to produce coherent output. Naturally, most artists skip this stage, as creating such algorithms requires some advanced programming knowledge, a massive imagery dataset, and an equally huge amount of computational power. Most of today's commercial image generators, such as DALL-E and Midjourney, are trained on virtually all artworks that could be scrapped from the corners of the internet and offer unmatched capabilities for creating stunning visuals, so you too can move straight to the creative part without filling your head with technicalities.
Prompting: surely the most fun part, where the user plays with text input to make the model spit out the artwork that most closely resembles the author’s creative vision. The process of carefully formulating instructions and tweaking them along the way gave rise to the so-called “prompt engineering,” which many may argue is an art on its own.
Fine-tuning: an optional step that is used by some artists to add the finishing touch to the AI-generated artworks with the help of the image editing software. In this stage, you may want to adjust the color palette, crop the image, and remove minor artifacts, such as extra fingers or unrealistic proportions.
Minting an NFT: the final step of creating an AI NFT is to encrypt the artwork and record it on the blockchain, a process known as minting. As NFTs are minted, the smart contract is first deployed on the blockchain to specify in code the properties of the token, such as royalties, ownership transfer rules, resale possibility, and other unique attributes. Next, the tokenized artwork is linked to the said contract. Once the NFT is minted, the creator can list it on a marketplace where it can be bought, sold, and transferred just like any other asset on the blockchain. It’s worth noting that although the above process sounds really complicated, most marketplaces have user-friendly interfaces that allow anyone to mint an NFT in a few clicks without any programming knowledge.
Although the last step is required to create an NFT, it’s completely optional if you need it for other purposes that don’t involve blockchain, such as making a cute illustration for your blog or elevating your social media presence with a unique avatar. Still, minting an artwork as an NFT carries many benefits for the artists, namely earning royalties from every resale, new ways to engage with the fanbase, and protecting their intellectual property from theft.
Leveraging Generative AI for advancing NFTs
Beyond any doubt, the intersection of AI and NFTs has already profoundly impacted the digital art landscape, but bringing machine-generated imagery to the blockchain is really just the tip of the iceberg. Surely, there are other, less obvious ways to combine AI and NFTs for maximum synergy of the two technologies. Let’s take a look!
AI used to generate NFT art: probably the most obvious and straightforward way to create stunning visuals using text input from the user and some optional tweaking to achieve the most impressive results.
Generative AI natively embedded into NFTs: a step further into the direction of a complete integration of AI and NFTs. Packaging AI with NFTs will open previously unthinkable ways to interact with the artwork, such as chatting with it, changing its appearance, using it as an in-game item across multiple platforms, or even keeping it as a virtual pet.
AI incorporated into NFT infrastructure: one of the most intriguing and underexplored dimensions. Successfully integrating AI tools into the existing NFT infrastructure will incorporate machine creativity into every stage of the NFT lifecycle, severing artists’ dependence on third-party services and streamlining NFT listing and minting. Platforms such as Recktangle are starting to tap into this trend, unleashing a new wave of artistic expression, combining the recent developments in the field of generative AI with the state-of-the-art marketplace.
The future of Generative AI x NFTs
AI is already transforming nearly every industry, and the NFT market is no exception. Today, AI-generated NFTs are slowly but confidently carving their niche in the digital art ecosystem and will become even more widespread in the future as the machine learning algorithms become more advanced and more infrastructure providers such as Recktangle are incorporating AI capabilities into their platforms.
