AI integration is helping Web3 become more dispersed, fortified, and user-focused. By incorporating AI functionalities across several aspects of Web3, we can anticipate the emergence of more intelligent, streamlined, and customized digital encounters. 

Web3 tools can efficiently evaluate large amounts of data using AI approaches like machine learning and natural language processing. It gives users predictive analytics, sentiment analysis, and personalized suggestions to comprehend decentralized dynamics and navigate the landscape.

AI in web3

Over the past decade, big tech has employed AI models to mine consumer data for insights and value. With Web3, the experts are expanding AI's utility beyond the reach of the wealthy few and into the hands of everyone. The creator's unique set of interests, experiences, and insights inform the training of every AI model.

A small number of private corporations monopolize the production of content and derive financial gain from it. As a result, content creators frequently need more compensation and are disregarded. Within the Web3 framework, producers possess complete autonomy over their data, AI models, and digital assets. Only a few organizations are actively involved in constructing blockchain systems, which grant creators exclusive control and authority over their data, enabling them to repurpose or share it according to their preferences. 

Security and privacy

AI can increase Web3 security through anomaly detection, automated smart contract analysis, data privacy through AI-driven encryption, and user experience through machine learning algorithms.

Advanced AI can improve Web3 ecosystem cybersecurity and data privacy. AI models may find weaknesses, hateful conduct, and anomalies in large data sets. Phishing and DDoS attacks can be prevented via machine learning. Moreover, AI builds consumer trust in Web3 platforms and apps by proactively securing them.

Web3 Alternatives to Web2 Platforms

Online content marketplaces have effectively addressed significant challenges by facilitating the convergence of vendors (offering products or content) and consumers. Nevertheless, the solution provided by the Web2 platforms could have been more reliable. The problem of monopoly arose immediately when marketplace platforms like YouTube, Spotify, Facebook, and others grew excessively large.  

After several years, we now possess a solution known as Web3, which purports to tackle the difficulties encountered in Web2. For example, DIMO is a platform that purports to provide a substitute for Uber, whereas Hivemapper attempts to enhance the accessibility and community involvement of Google Maps. Let us examine the various choices and delineate their distinctions from conventional applications. 

Hivemapper

Hivemapper is a distributed network for creating maps that can be used as an alternative to centralized systems like Google Maps. Hivemapper is a decentralized mapping platform that uses money as an incentive for map authors to increase map coverage, frequency of updates, and quality.

Audius

Audius is a distributed music platform that prioritizes artists' freedom of expression and financial autonomy. Audius is an alternative to services like Spotify that provide creators more control over their work and more of the cash generated from sales. 

Presearch

The decentralized search engine Presearch aims to incentivize users to perform searches on the platform. Presearch, in contrast to Google, promises a more versatile search experience by letting users choose between numerous platforms and search engines. 

DIMO

DIMO is a platform that operates decentralized and is driven by the community. It presents a novel perspective on the future of mobility. DIMO differentiates itself from conventional ride-hailing platforms such as Uber by prioritizing driver empowerment by providing data-sharing options and long-term rewards. 

Image source: Unsplash