AI in Web3: How AI Manifests in the World of Web3

What Is Web3?

Web3 refers to the third generation of the World Wide Web, which aims to create a decentralized and more transparent internet infrastructure that allows for trustless interactions between parties without relying on intermediaries or central authorities.

The term “Web3” is often used to describe the development of decentralized applications (dApps) that utilize blockchain technology, such as Ethereum, to create trustless smart contracts and execute transactions in a secure and transparent manner. These applications can range from digital currencies to social networks, gaming platforms, and other forms of decentralized finance (DeFi) applications.

Overall, the goal of Web3 is to create a more open and decentralized internet, where individuals have more control over their data and online interactions and where trust and transparency are built into the infrastructure itself.

What Is AI?

AI stands for artificial intelligence, a branch of computer science that focuses on developing intelligent machines that can perform tasks that normally require human intelligence, such as perception, reasoning, learning, and problem-solving.

AI is based on the idea of creating algorithms and systems that can learn from data, identify patterns, and make decisions based on that learning. The field of AI encompasses a wide range of technologies, including machine learning models, deep learning, natural language processing, robotics, and computer vision.

Some common examples of AI in use today include speech recognition, image and facial recognition, recommendation systems, and autonomous vehicles. AI has the potential to revolutionize many fields, including healthcare, finance, education, and manufacturing, among others. However, there are also concerns about the potential risks and ethical implications of AI, particularly as it becomes more advanced and autonomous.

How AI in Web3 Makes Layers of Web3 Intelligence

AI can play a crucial role in creating layers of intelligence in Web3 applications. These layers can be considered different levels of abstraction, each providing a higher level of intelligence and functionality than the previous layer. Here are some examples of how AI Web3 can be used to create these layers:

Intelligent blockchains

These days, most blockchain systems are devoted to perfecting the distributed computing building blocks that make the decentralized handling of monetary transactions possible. Consensus methods, mempool structures, and oracles all fall under this category of fundamental building components. Just as existing software infrastructure building blocks like storage and networking are becoming more intelligent, the next generation of layer 1 and layer 2 blockchains (companion and base) will contain ML-driven capabilities.

For instance, a blockchain runtime may leverage ML prediction in transaction processing for the sake of developing scalable consensus procedures. Blockchains can benefit from AI’s security features, as AI applications can swiftly mine data and predict behavior to identify fraudulent activity and cyberattacks. Also, an AI protocol could potentially foresee transactions and design scalable consensus methods, both of which would be very useful to the blockchain.

Intelligent protocols

The usage of smart contracts and protocols in the Web3 stack allows for the incorporation of ML capabilities. Perhaps the best example of this trend is DeFi. Soon, automated market makers (AMMs) or lending protocols will be available in the DeFi market that include ML models in their decision-making processes. One such application is a lending protocol that employs a smart score to distribute funds evenly from various wallets.

Intelligent dApps

Web3 solutions that allow for the quick addition of ML-driven functionality will likely include decentralized apps (dApps). There is already evidence of this trend in NFTs, and it will only increase. In the future, NFTs will evolve from mere images to interactive artifacts with complex intelligence. These NFTs may eventually modify their actions based on information about their owners’ emotional states.

Why AI in Web3

Shift from generalization to individualism

During the past decade, many large technology companies have relied on centralized AI models to mine user data for insights and value. In Web3, we are expanding AI’s powers to benefit everyone, not just the rich. Each AI model is built from the ground up using the creator’s unique set of experiences, interests, and knowledge.

From users to owners

Only a select few private corporations have the power to monetize user-generated content. As a result, many people who create material are compensated poorly or are ignored. In the world of Web3, creators own all their information and creations, including any AI models and digital assets used in them. Since very few corporations assist in the development of blockchain platforms, producers retain complete control over all the data and can use it for whatever purpose they see fit, including redistributing it.

From scarcity to utility

Tokens are insufficient to give consumers ownership or incentives necessary for long-term viability. Tokens should serve a purpose and be of genuine value to their holders. As you create content using your own unique brand of ingenuity and smarts, your personal AI unlocks entirely new forms of value. Access and involvement allowed by social tokens allow your personal AI to open new avenues for collaboration and produce value for you and your community.

From consumption to participation

Present-day media distribution systems are geared toward large numbers of users, and communication between producers and viewers is a one-way street. With the advent of individualized AIs and decentralized social token economies, creators and their communities now have a dedicated space to share their work and conduct commerce. Through our innovative architecture of collaborative networks, we aim to change the dynamic between value production and consumption.

Subscriptions and investments

Over the course of many years, creators have sought to amass a considerable subscription base from which they may profit. Unfortunately, only a small percentage of creators actually make a living salary, which is bad news for both them and their fans. The rise of AI in Web3 is fueling a new creative economy, where fans can financially support their favorite artists and developers as well as the AIs that make their daily life easier. Now more than ever, artists can make a living from their craft, and everyone wins when they succeed.

How Can Artificial Intelligence Be Used in Web3?

Using AI in web app interface design will result in improved usability. For example, Web3 AI can be used to better select which website content to feature. Additionally, AI can potentially enhance search engine rankings.

Existing applications of artificial intelligence in Web3 are promising. One application of AI is on the website Suggesto, which uses the data users have provided about their preferences to recommend articles and videos. Presearch, a search engine that uses AI to deliver more relevant results based on a user’s preferences and past activity, is another example.

We should expect to see even more creative applications of AI in Web3 as more and more people start playing around with it. Thus far, AI has shown promising results in enhancing online experiences.

The Benefits of Using Artificial Intelligence in Web3

AI can potentially bring several benefits to Web3 applications and blockchain systems. Here are some of the key benefits of using AI in Web3:

• Enhanced security: AI can detect and prevent fraudulent activities, identify security vulnerabilities, and mitigate security risks. AI algorithms can also help to identify suspicious behavior and alert users in real time, improving the overall security of Web3 applications.
• Improved efficiency and scalability: AI can optimize transaction processing and reduce the time and resources required for verification and validation, improving the efficiency and scalability of Web3 applications.
• Intelligent automation: AI can automate complex tasks and decision-making processes, enabling Web3 applications to operate autonomously and more efficiently. For example, AI can automate smart contract execution, manage funds, or perform other tasks that humans typically handle.
• Decentralized decision-making: AI can facilitate decentralized decision-making and governance, enabling stakeholders to collaborate and make decisions more efficiently. This can include using AI to create collective decision-making processes or creating AI agents to collaborate and solve complex problems.
• Predictive analytics: AI can perform predictive analytics, enabling stakeholders to make informed decisions based on data-driven insights. This can help to improve the accuracy of market forecasting, risk management, and other key business decisions.

Overall, the use of AI in Web3 has the potential to improve the functionality, efficiency, and security of blockchain systems, making them more effective and better suited to meet users’ needs.

When Web3 Will Use AI

Now that we understand how AI and Web3 work, it’s time to learn when to expect them. The development of AI systems is advancing at a breakneck pace, and fascinating new Web3 products are being created every day.

But that doesn’t imply we can predict precisely when Web3 and AI will enter the mainstream. Most individuals don’t mind having their information, power, and apps all in one place right now.

Nevertheless, that won’t hold true indefinitely. It’s risky to put so much trust in centralized authority, which can cut off access to any network at any time, as many people are beginning to realize.

Why Does Web3 Follow the Top-Down Adoption of ML Technologies?

Web3 intelligence’s layers suggest a base-up adoption tendency. Blockchain runtimes may become smarter, affecting NFTs and DeFi protocols. Web3 must adopt ML technologies hierarchically due to technological constraints. Since blockchains are distributed computing, designing new blockchain runtimes creates technological barriers.

This approach differs from cutting-edge ML models, which require complicated, long-running calculations to develop and streamline concepts for a unified design. Blockchain runtimes can integrate native ML. This requires several iterations.

DeFi protocols can take advantage of existing ML systems by using external intelligent specialists and oracles. NFTs and dApps have few restrictions. This shows that Web3 will embrace ML core capabilities hierarchically, from dApps and protocols to blockchain runtimes.

Conclusion

The use of AI in Web3 is a cutting-edge development. The first signs of intelligence in Web3 apps are starting to appear. We may state categorically that Web3 is intelligent, but this intelligence is not uniformly dispersed.

Our Web3 specialists are available to assist you in developing your own platform and an AI-enabled Web3 product. Contact us today to talk about what you need from your next smart solution.