AI in web3 - the paradigm of AI adoption in web3

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Experts predict that AI/ML will influence a wide range of technologies and industries, and web3 is no exception. However, there are technical hurdles that web3 technologies must overcome to adopt AI. It is therefore important to understand how AI can be integrated into web3 technologies overcoming the major obstacles preventing this from happening. If we deeply look into AI in web3, AI-based solutions are currently primarily centralized. The real question is: what role will AI play in the new decentralized web3 world, considering all the hype around it? How can we unravel AI's tendency to centralize? This article will go into the details of AI in Web3.


Web3 - an overview

Web3 is a high-level concept that describes the future internet. It is about sharing power and benefits via decentralization. When web3 is fully functional, it will free the internet from the centralized control of a handful of large technology companies. Users will be able to control their data, resulting in greater privacy. There will not be any censorship, and all rewards will be equally distributed. These are web3's most distinctive characteristics, even though it still needs to be standardized.

Decentralization has been a core principle of web3. Web2 uses HTTP to locate information, and this is done using a unique web address. Web3, being blockchain-based, would allow information to existing in multiple places across a network. Users would have more control over the huge databases held by internet giants like Google and Meta. Alongside, web3 will enable users to sell data from different computing resources, such as mobile phones and desktops, if they desire so. In web3, users retain complete control of their data.

Permissionless, trustless and anonymous: Web3 uses open-source software, and it is decentralized. Web3 apps that are built on blockchains are known as dApps.

Artificial Intelligence (AI) and Machine learning: Web3 uses technologies based on Semantic Web concepts and natural language processing to allow computers to understand information as humans. Web3 will also use machine learning, gradually improving its accuracy. These capabilities enable computers to produce more relevant and faster results in many business areas.

Connectivity: Information and content are more connected to web3 and can be accessed by multiple applications. There is also an increase in devices that can connect to the internet, and the Internet of Things plays an important part in this.

How AI in web3 creates layers of web3 intelligence?

ML (Machine Learning) is an integral component of AI, and web3 will add ML to various layers of its web3 stack. The following three web3 layers are capable of providing ML-driven insights.

Intelligent blockchains

Blockchain platforms are currently focused on developing key distributed computing components that enable the decentralized processing of financial transactions. These building blocks include mempool structures, oracles, and consensus mechanisms. The next generation of layer1 (companion) and layer2 (base) blockchains will include ML-driven capabilities. This is just as traditional software infrastructures such as storage and networking are becoming increasingly intelligent. A blockchain runtime can use machine learning prediction to make transactions and create consensus protocols. AI applications can rapidly mine data and predict behavior, which can help detect fraudulent behavior and stop attacks. AI will benefit the blockchain as an AI protocol that can predict transactions and create consensus protocols that can be scaled easily.

Intelligent protocols

Web3 stack can also integrate ML capabilities via smart contracts and protocols. DeFi most clearly illustrates this trend. It is not far from computerized market makers (AMM) or lending protocols that use more intelligent logic based on ML models. For example, a lending protocol that uses intelligent scores to balance loans across different types of wallets can be imaginable.

Intelligent dApps

Decentralized apps, which are fast adding ML-driven features, are expected to be the most popular web3 solutions. This trend is already apparent in NFTs and will only continue to grow. NFTs of the next generation will be able to transform static images into artifacts that exhibit intelligent behavior, and these NFTs can adapt to their owners' moods.

Why AI in web3?

Shift away from generalization and towards individualism

Over the past decade, big tech has relied on centralized AI models to extract value and gain insight. There is continuous advancement of AI capabilities so that everyone can benefit from it, not just a few. Each AI model is trained on its creator's passion, knowledge, and experience.

From users to owners

Only a few private companies have the right to control all content and make a profit. Content creators are often underpaid and left behind. Web3 creators fully control their data, AI models, and digital assets. Few companies have helped to create platforms on blockchain. This means that creators have sole access to their data and the power to reuse or share it however they want.

From scarcity to utility

Tokens cannot be used to grant users ownership or incentive. Tokens should be useful and offer real value to users. Your personal AI unlocks and creates new value through the content, creativity, and intelligence you use to create it. Through social tokens, your personal AI opens up new possibilities for collaborations. It creates value for yourself and your community by enabling access and participation.

From consumption to participation

Platforms today are designed for mass consumption. Content creators create content, and the audience consumes it. Thanks to their personal AIs, creators and their communities can have their platforms. They also have their way of exchanging value using social tokens. A new architecture is in process for collaborative networks that shifts power away from platforms to people and transforms the relationship between value creation and value consumption.

Investments and subscriptions

Creators have always hoped for a large subscriber base over many decades and eventually monetize that subscriber base. The reality is that very few creators make a decent living, which is bad for both creators and their subscribers. AI in web3 is driving a new creator economics that allows communities to invest in creators they care about and personal AIs that bring value to their lives. The community can now benefit from the success of creators who can create a sustainable business around creativity.

Final word

AI in web3 is a futuristic technology trend. The rapid development of ML technology has led to an abundance of ML platforms, frameworks and APIs that can be used for intelligent web3 solutions. We are already seeing instances of intelligence in web3 applications. Although intelligent web3 is a possibility, it can be challenging to find.

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