Generative AI technologies such as ChatGPT and Copilot have made significant progress in the past few years, demonstrating outstanding performance in fields such as natural language processing, image generation, and speech synthesis.
NFT, short for Non-Fungible Token, is a type of digital asset based on blockchain technology, where each NFT is unique and cannot be exchanged or replaced. Unlike other cryptocurrencies such as Bitcoin and Ethereum, they do not have equivalent value. NFTs can represent digital artworks, virtual properties, music, videos, and game items, among others, and their uniqueness and non-fungibility have made them a popular product in the digital asset market.
With the rise of NFTs, the applications of generative AI technologies are constantly increasing. AI tools such as ChatGPT and Copilot are receiving more attention in the use of NFTs, bringing significant opportunities and challenges to the Web3 ecosystem.
In this article, we will analyze specific examples of how artificial intelligence is applied in NFTs in detail.
AI-generated content introduction
Recently, DALL-E and ChatGPT-4 have become a sensation on the internet, with the former being able to generate “impressive visual assets” and the latter being able to conduct “human-like conversations”. Meanwhile, Microsoft’s upcoming product Copilot has caused mass human panic due to the powerful functions demonstrated in its promotional videos, leading to fears of being replaced by artificial intelligence.
AIGC (Artificial Intelligence Generated Content) has recently been hailed as a revolutionary phenomenon that is taking the internet by storm. But what is it exactly?
AIGC refers to content that is automatically created by artificial intelligence algorithms, often based on extensive training on large datasets, and has high levels of automation and efficiency. These models are capable of generating various types of content, such as news reports, advertising copy, music, and videos.
In contrast to PGC (Professionally Generated Content), which is created by professionals such as journalists, writers, photographers, and artists, AIGC requires less human intervention, as the content is automatically generated. This reduces the costs and time associated with hiring individuals to create the content. With advancements in technology, ChatGPT-4 has high natural language generation capabilities, which enable it to produce more realistic and natural language texts.
Furthermore, AIGC is typically generated based on extensive datasets, which can better meet users’ personalized, and recommendation needs. Through data analysis and mining, AIGC can better understand users’ interests and preferences, generating content that is tailored to their needs.
Specific Examples of the Combination of AI and NFT
Despite the risks and opportunities that coexist, while generative AI still cannot replace humans and has limitations that need improvement, we must believe in the speed of machine learning and the constantly evolving times. Only by truly understanding what AI can do can we know how to better utilize AI in the Web3 domain.
Due to the length of this article, we will focus on the combination of AI and NFT. In the field of graphic and music streaming, AI’s growth rate is astonishing, comparable to combining da Vinci with Mozart and acquiring Zhang Daqian’s skills, with the potential to revolutionize content creation.
NFTs generated by AI are called generative art NFTs. Artists first need to input a set of rules (such as color and pattern range) and parameters (such as iteration times and random degrees), and the computer will generate the artwork within this framework. This method makes it easier for artists to create unique digital assets.
For example, Art Blocks uses the “Curated Generator” algorithm to generate a series of artworks and turn them into NFTs. The virtual reality platform, Terra Virtua, allows users to buy and trade NFTs. And as mentioned earlier, DALL-E, also from OpenAI, is a language model that can transform text descriptions into images. DALL-E can generate various images, including people, animals, and scenes, and turn them into NFTs. In the Metaverse, AI plays a role in combining various technologies such as blockchain, VR, and 3D animation. Assets are no longer created in traditional forms. With the rise of user-generated AI tools, authenticity can be verified.
Many readers may be familiar with Eponym, as it is one of the most popular NFT projects among enthusiasts. The project is developed by Art AI, the world’s largest AI-generated art gallery, which relies on personalized art generation through text-to-art conversion and helps users create NFTs based on the phrases or words they choose. Each text prompt can only generate one piece, which means Eponym creates truly unique works. The project has been hugely successful, with the first Eponym release selling out in just a few hours on OpenSea.
Moreover, AI can serve as an art appraisal standard and provide more precise and fair value evaluations for NFT artworks. For example, by training models, AI can identify and evaluate various elements of artworks such as color, composition, and lines, providing a more scientific and objective price for these NFT artworks.
AI can generate high-quality graphics such as characters and scenes through training, providing a faster and more efficient creative process for fields such as game development and movie special effects. NFTs can provide unique digital asset identifiers for these AI-generated graphics, giving them unique value and collectibility.
It is worth mentioning that AI can not only generate still images but also create music, especially in the field of electronic music. By training models, AI can imitate various music styles and create artistic works. Some well-known music-generating AIs include AIVA, a music-generating AI developed by a French startup that can automatically generate original music, and Amper Music, whose platform uses deep learning algorithms to generate original music.
In the future, NFTs can provide a complete copyright protection and transaction system for the music generated by these AIs, creating a more fair and transparent music industry ecosystem.