How Does AI Contribute To Web3 Intelligence?

In this post, we’ll take a trip down the rabbit hole and talk about how AI fits into the Web3 environment.

We are on the threshold of a new technological era, and experts predict that AI and machine learning (ML) will soon form the backbone of a vast majority of the world’s software.

According to PwC, artificial intelligence would boost global GDP by 14%, or $15.7 trillion, by 2030.

Database and identity management advancements, along with AI, are further solidifying intelligence as the foundation of today’s software systems.

A Symbiotic Relationship: AI AND WEB 3

Machine learning (ML) is revolutionizing our approach to fundamental tenets of software infrastructure, from cloud computing to networking. Web3, the most recent incarnation of the World Wide Web, is no different in this regard. Machine learning is set to play a crucial role in promoting AI-based Web3 technologies as Web3 becomes more widely used.

The incorporation of AI into Web3 does, however, pose several technological difficulties. Therefore, to liberate the full potential of AI in Web3, we must first identify the barriers to this convergence and develop creative approaches to removing them.

As we go deeper into the decentralized realm of Web3, the issue arises: how can AI adapt to and survive in this new setting, shedding its centralization tendencies?

Centralization has long been the standard for AI-based solutions.

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 List of AI web3 companies

• PARSIQ
• Weld
• Golem
• Spice AI
• Unstoppable Domains
• ChainML
• Kosen Labs

Layers of Web3 Intelligence and How AI Contributes to Them

When talking about AI, ML is essential. The integration of ML to Web3 will permeate the whole Web3 stack. Insights powered by ML may be obtained from three essential Web3 layers.

Intelligent blockchains

To facilitate the decentralized processing of financial transactions, current blockchain systems are concentrating on creating critical distributed computing components. Consensus methods, mempool structures, and oracles are all part of these fundamental building elements.

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 features.

Intelligent protocols

Using smart contracts and protocols, the Web3 stack may also incorporate ML capabilities. DeFi is the best example of this pattern.

Defi automated market makers (AMMs) or loan protocols with smarter logic based on ML models are on the horizon. Imagine, for instance, a lending protocol that employs a smart score to distribute funds from several wallets.

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Intelligent dApps

One of the most promising Web 3.0 approaches to incorporating ML-driven functionality quickly is the creation of decentralized apps (dApps).

There has been and will be a growing pattern of this in NFTs. The next generation of NFTs will evolve from simple pictures to interactive objects. These NFTs could be able to modify their actions depending on the owner’s emotional state.

Autonomous Agents

By supplying Autonomous Agents with real-time data and a set of established rules, Web3 platforms can improve the efficacy of smart contracts.

In addition, these agents may carry out transactions, make agreements, and deliver individualized care. Using such agents automates labor-intensive tasks, reduces the need for middlemen, and benefits Web3 as a whole.

Personalization

AI plays a crucial role in the Web3 environment in creating personalized user experiences by analyzing data, analyzing interaction patterns, and analyzing preferences. To improve several aspects of Web3 platforms, AI makes use of collaborative and content-based filtering methods to generate individualized suggestions.

By catering material and interactions to each user’s specific interests, this type of customization boosts user participation in Web3’s decentralized ecosystem while also improving the efficiency of content discovery and curation.

Insights & Analytics

Incorporating artificial intelligence techniques like machine learning and natural language processing, Web3 networks can quickly handle and evaluate massive amounts of data.

This gives consumers the ability to better comprehend decentralized dynamics and navigate the environment through the use of predictive analytics, sentiment analysis, and tailored suggestions.

Safety & Confidentiality

Using cutting-edge AI methods, Web3 ecosystems can enhance cybersecurity and protect user data privacy. Artificial intelligence models can sift through mountains of information in search of security flaws, bad actors, and outliers.

Cybersecurity risks like phishing and distributed denial of service (DDoS) assaults can be thwarted using machine learning algorithms. AI improves users’ faith in Web3 platforms and apps by proactively securing them.

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FAQs: Web3 And AI

• What are the trends and future predictions of the Web3 wallet?

Blockchain will be utilized in the future for a wide range of tasks, including supply chain management and personal data security. Decentralized Finance (DeFi): One of the most popular Web3 ideas is DeFi. It enables you to take charge of your money and stop depending on conventional institutions.

• How does web3 work?

Cryptocurrency is used by a Web3 protocol to encourage individual users worldwide to manage the platform. By engaging in direct transactions with other peers on the network, Web3 users may take advantage of the technology to monetize their goods and services.

• Are web3 and Metaverse the same thing?

A decentralized version of the internet is envisioned by Web 3.0. Virtual environments that allow for online social interaction through digital avatars are referred to as the “metaverse”. We’re going to see more metaverse settings utilizing web3 technologies as they evolve.

• How is web3 different from the internet?

Web3, an improved version of the World Wide Web, is the next generation of the internet. Because its foundation is made up of decentralized technologies like peer-to-peer networks and blockchain, it is often referred to as the “semantic Web” or the “decentralized Web.”

• How can Web3 technology be used to improve data privacy and security?

A key component of Web3 is optimizing data privacy and security. Web3 makes use of blockchain technology to offer people ownership over their data. Users can have transparency over their identities and data records thanks to this peer-to-peer network.