The Intersection of Generative AI and Blockchain: Creativity Tokenization

Authored by: Kava Labs

We will continue to explore the integration of artificial intelligence (AI) and blockchain technology, with a focus on the role of generative AI and tokenization. As one of the most innovative yet controversial areas in AI and blockchain technology, we need to refer to previous articles on tokenization of RWA, natural language processing (NLP) in AI, and the role of AI in risk mitigation and cross-chain interoperability to fully understand the broader impact of the integration of these two technologies.

In this article, we will explore the powerful capabilities of generative AI, how it works, and the copyright material issues when tokenizing the output of generative AI. Then, we will turn to the role of blockchain technology and non-fungible tokens (NFTs) as potential solutions to these issues. We will also examine industries that have already utilized NFTs, and discuss the future potential of this dynamic field and the role AI may play at the end of the article.

The future of creating content

Like other aspects of the AI field, the evolution of generative AI has deep roots in the field of computer science, dating back to the 1960s. British artist Harold Cohen achieved early iterations of computer-generated imagery through his AARON project at the University of California, San Diego. However, despite these early iterations of generative AI imaging, it wasn't until the fourth quarter of 2022 with the launch of ChatGPT3.5 that marked the prosperity of modern AI and gave the general public an opportunity to experience this groundbreaking technology.

With the release of Midjourney, Leonardo.ai, and DALL-E in 2023, the popularity of generative image protocols has quickly exploded. Generative AI (GenAI) and prompt engineering have rapidly entered the public eye, while large language models (LLMs) have also attracted attention. Overnight, everyone has gained the ability to generate realistic images in a matter of seconds, a task that previously required a great deal of manpower and could only be completed by professional artists and photographers.

Since then, generative AI has made significant progress, iterating and improving early versions. Even traditional Web2 companies have begun implementing AI image generation and editing protocols, such as Photoshop's generative fill toolkit launched in May 2023. We have also witnessed the expansion of this field from images to audio, video, and 3D modeling.

How does generative AI work? Do traditional artists need to worry, and how does blockchain help generative AI?

Understand this technology

To determine the possible intersection of blockchain with generative AI, we first need to understand the working principle of this technology and whether it could be interpreted as plagiarism.

The first step in generative AI is the same as other AI models - collecting, indexing, and cleaning raw data. Generative AI collects image, audio samples, videos, or 3D digital models. Then, the model can be trained to recognize objects, textures, colors, and audio patterns.

Once the model decomposes its sample data into the most basic components, it can be used to reconstruct and replicate patterns and dependencies, such as how colors interact and the spatial relationships between objects. Similar to how large language models use probability models to predict the next word, sentence, or paragraph, generative AI uses probability models to predict pixel values and their positional relationships, combining them into a single coherent image output.

The final stage of generative AI is to use these outputs in its feedback loop. By iterating and improving the model, more accurate outputs are created over time.

The controversy over copyright has become blurred as models can be trained on open-source data and do not directly replicate any single original data. They use highly complex predictive models based on billions of original data touchpoints and combine them into an output through predictive modeling. One way to think about it is that these models are more like modern singers who may be influenced or inspired by Michael Jackson or The Beatles, rather than directly covering their songs.

The Rise of NFTs

NFT first appeared in 2014 when digital artists Jennifer and Kevin McCoy minted Quantum on the Namecoin blockchain. In 2017, NFTs gained a niche following with the release of CryptoKitties, and in the bullish market of 2021, they became popular with projects like Bored Ape Yacht Club, CryptoPunks, as well as independent digital artists like Beeple.

In the bull market of 2021, NFT demonstrated the powerful functionality of its underlying blockchain technology use cases. The immutable decentralized ledger can solve the long-standing problem of establishing coherent source proofs. Various industries can easily determine the legitimate ownership of their products by possessing a permanent and unchangeable digital authentication seal. The high-end art database Artory has performed well in using blockchain technology to establish source proofs for exclusive artworks.

Since the NFT boom peaked in 2021, the popularity of NFTs has declined, but their importance has not diminished. The introduction of dynamic and non-fungible NFT projects through the ERC-721 and ERC-1155 token standards has created new markets, especially with the rise of Real-World Assets (RWA). The tokenization of real-world assets, particularly in the real estate and automotive industries, benefits from the ability to establish coherent proof of origin and update NFTs over time to reflect maintenance and improvements.

Mint NFT

In the bull market of 2021, NFTs became popular due to the ease of creating NFT series. For a fast-growing industry that is relatively niche and has technological barriers to entry, being able to mint NFTs on platforms such as OpenSea and Rarible provides a simple entry point for millions of users. Setting up a wallet may be more challenging compared to creating your own NFT series.

The initial setup is completed through a simple account creation process. Once the user connects the wallet to their account, they can easily upload and mint a series within minutes, similar to the convenience of uploading images to a cloud provider. The user experience is unparalleled, and once their images are approved, they can easily trade between the platform and their chosen exchange.

Liquidity of Digital Art

The ability to mint NFTs and freely buy and sell digital artworks is an important step in attracting millions of users. While this serves as a crash course in the volatility of the cryptocurrency market, more importantly, it provides users with a dynamic educational tool. They quickly understand and start implementing cryptocurrency trading. For example, they can seamlessly transfer from NFT platforms to wallets and exchanges, and then convert back to fiat currency.

This also allows many creators to monetize their digital artworks for the first time. This reflects the fundamental promise of Web3, which is to return financial and creative sovereignty to individuals, rather than third-party gatekeepers.

The New Era of Royalties

One aspect of the origin of digital assets that NFTs often overlook is their ability to automatically pay royalties to the original creators. Although the concept of Artist Resale Rights (ARR) or droit de suite has been around since it was first introduced in France in 1920 at the beginning of the 20th century, this is still a relatively new practice for many countries.

In this respect, NFT provides a unique opportunity. For any particular NFT transaction, the automatic implementation of royalties addresses this issue without any cumbersome traditional intermediaries. The curation process of the NFT platform returns this power directly to the creators, enabling them to determine the percentage of royalties they wish to receive.

The future of AI and NFT

One impressive aspect of the rise of NFTs in 2021 is that it has not relied on generative AI protocols. In that environment, digital artists flourished, but now anyone can easily create high-production-value artwork like using a chatbot. Therefore, the future profitability of this market is unclear. People may pay more attention to the practicality and community of the project.

The generative AI protocol can turn individuals into outstanding artists and open up career opportunities that were previously out of reach. However, a major issue that artists faced in the previous cycle was that their artworks were sold as NFTs without their consent. There is still legal ambiguity regarding the monetization of digital assets created through generative AI protocols. These two factors could come into conflict, especially if generative AI assets are used to create generational wealth through popular NFT series.

In the previous cycle, when NFTs were copied and minted on multiple blockchains, plagiarism also played a role in fueling the fire. The issue of lack of interoperability and data silos has been discussed in previous blog posts. In this regard, AI can play an important role. Through security enhancements such as early anomaly detection and fraud prevention, AI can serve as a support, just like in the field of RWA and DeFi. This is crucial for establishing cross-chain interoperability security when determining the source of digital assets.