The evolution from the current generation Internet (“Web2”) to the next generation Internet (“Web3”) represents a fundamental paradigm shift in the way information on the Internet is managed and controlled. Although there is no single accepted definition for Web3, the term refers to a decentralized internet that leverages blockchain technology to put control of data back into the hands of users, reducing the power currently wielded by big tech companies. often used to refer to Web3 offers potential solutions to problems such as lack of privacy, surveillance, and misinformation created by a data-hungry society where consumers are often a commodity. However, adoption of Web3 has been hampered by significant user friction.
The integration of AI and blockchain technology can provide the catalyst needed to accelerate the adoption of Web3. The technological synergy between AI’s ability to learn and make predictions from data and blockchain’s transparent, tamper-resistant data processing capabilities can improve the Web3 user experience and reduce user friction. Masu. For example, decentralized AI built on blockchain can provide users with customized online experiences, such as music recommendations based on their past listening history, without sacrificing privacy or control over their personal data. .
The power of AI and blockchain in Web3
Blockchain and AI are complementary technologies, each offering solutions to the problems the other poses. In the field of AI, access to high-quality data is essential for designing and developing effective and accurate AI algorithms. AI trained on flawed data will inevitably produce flawed results. This is also called “garbage-in.” “Take out the trash” problem. Consensus protocols built into blockchains are a way for nodes on the blockchain to agree on the “truth” of data, helping to reduce “garbage contamination.” Solve the “garbage out” problem by enabling verification of data authenticity, accuracy, and completeness. Decentralizing authority over data and algorithms can also prevent power over AI from becoming concentrated in the hands of a few companies. As Securities and Exchange Commission Chairman Gary Gensler said in a recent podcast on AI and the financial sector, “hundreds and thousands of financial actors who rely on central data and centrally selected models” are “undermining this society. The financial sector as a whole can pose risks to society. ” As a decentralized system, blockchain platforms can be designed to allocate power in a way that reduces the risks arising from a small number of AI companies and models making opaque but consequential decisions.
Fusion of AI and blockchain
However, harnessing the power of AI and blockchain in tandem has not been easy, and technical challenges have taken time to overcome. One useful way to chart the joint development of these two technologies is through the lens of a three-phase progression: from data (Phase 1) to information (Phase 2) to knowledge (Phase 3) . Basically, data consists of raw alphanumeric values, and information is structured and organized data. Knowledge represents the collective insights and takeaways extracted from information. But sifting through mountains of data and information to extract actionable insights can be difficult.
Until recently, blockchains were not originally designed to optimize searchability, making searching, indexing, and extracting data complex, especially across diverse formats such as text, audio, and images. But companies like The Graph, often likened to the “Google of Web3,” are moving ahead with Phase 1 of leveraging indexable and searchable data from blockchains without relying on centralized intermediaries. I have mainly been working on issues.
In Phase 2, companies with access to large amounts of blockchain data shifted their focus to organizing this data into coherent and analyzable information. This has been difficult because blockchain provides a public record of transactions between wallet addresses, but those wallet addresses, by design, cannot easily trace real-world identities. A wallet address is a cryptographically generated string that acts as a pseudonym for a user. Therefore, it was difficult to extract useful information from this data for due diligence and analysis purposes. However, many companies like Nansen have stepped in to address this void, providing a means to glean valuable information from blockchain data that can be used to train AI algorithms.
But the next frontier, or “phase 3,” is to develop knowledge from the vast amount of information provided by blockchain platforms. This challenge has not yet been fully resolved, as the task of meaningfully connecting disparate data and information is time-consuming and manual. AI can be a powerful tool to automate the difficult tasks of extracting, organizing, storing, and distributing an organization’s collective knowledge.
AI can accelerate Web3 adoption by delivering personalized experiences
Generative AI has exploded in popularity recently because it can provide customized experiences based on user prompts. Hanjin, his CEO of his AI-driven Web3 company Bluwhale, said: “For Web3 to become mainstream, the next generation of consumer applications using blockchain will need to at least match the user experience of Web2. Personalization will not be an option, but a necessity. ” This approach allows decentralized applications to more effectively engage their current audience, attract new users, and thereby optimize their marketing spend.
A knowledge graph, or what Jin calls a “decentralized AI brain that scales across blockchains,” could be the missing component to bring the personalized experiences of Web2 to Web3. A knowledge graph is a data science tool that maps relationships between objects, facts, events, situations, and other data. Knowledge graphs are often used in conjunction with AI because they help give meaning and structure to diverse datasets. Search engines often use knowledge graphs to help computers understand the context of people’s queries and connect billions of facts about people, places, and things.
However, like Web2’s core infrastructure, much of the knowledge graph is built by centrally managed entities, siled to specific organizations, and not widely shared. Decentralized knowledge graphs, like the one being built by OriginTrail, make knowledge graphs more accessible by leveraging open, permissionless blockchain networks where the public can contribute, maintain, and verify knowledge.
The future of the Internet will be built on emerging technologies
By leveraging cutting-edge tools such as knowledge graphs, the integration of AI and blockchain can serve as the foundation for a Web3 built on trusted data. This new decentralized internet will help address issues prevalent in today’s centralized internet, including disinformation, surveillance, risks to privacy and security, and a total loss of agency over personal data.
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