Can the combination of AI and Web3 lead to a new data revolution?
QnA3 is a data engine based on AI large models and Web3 knowledge graphs. Users can ask any questions related to Web3 in QnA3, and it will search its vast knowledge base through AI to provide the most accurate answers.Author: QnA3
Web3 addresses the fairness and ownership of data, with all on-chain data being publicly transparent and not belonging to any trusted third party. AI provides a new paradigm for data integration and analysis, breaking through the traditional ways users search for and interact with data.
In this era of information explosion, for Web3 practitioners or participants like you and me, we face a massive influx of new information every day: What happened with Azuki? Is the Bitcoin spot ETF coming back? Didn't FTX go bankrupt, so how is it appearing again? In such a torrent of information, we sometimes feel overwhelmed, needing to grasp the details while not losing sight of the big picture, trying to find valuable information amidst the endless data, which is like searching for a needle in a haystack.
The vast and complex amount of information, obscure jargon, and scattered and chaotic data sources often deter many new friends wanting to understand Web3. The early rapid and wild development of Web3 has made these issues even more prominent, as most "outsiders" cannot quickly grasp the full picture of an industry, project, or event, and can only follow the steps of some KOLs, entering the Web3 field step by step.
At this moment, the emergence of AI large language models has revealed that through their data analysis and processing capabilities, we can extract truly valuable knowledge from complex information, providing deep insights that give us more confidence in the decision-making process. When this capability is combined with the Web3 field, it will trigger a revolution within the industry:
- Intelligent Decision Support: AI can deeply interpret various data and market dynamics, helping us quickly grasp key information and make precise decisions in this rapidly changing Web3 world.
- Optimized User Experience: Through AI, we can provide personalized information and services based on historical behavior and preferences, meaning we can more easily access information that truly matters to us without sifting through vast amounts of data.
- Increased Industry Efficiency: With AI's analytical capabilities, we can effectively integrate various Web3 data, uncovering potential market patterns and trends, which not only helps us better understand the market but also enhances the operational efficiency of the entire Web3 industry.
QnA3's vision is to utilize the Chain-of-Thought capabilities of large language models to construct a large knowledge graph from the complex data in the Web3 world, allowing Web3 users to quickly access information through AI large language models.
On June 25, 2023, QnA3 launched version 2.0, introducing an AI large language model-based Web3 knowledge Q&A feature.
What is QnA3?
QnA3 is a data engine based on AI large models and Web3 knowledge graphs. Users can ask any questions related to Web3 in QnA3, and it will search its vast knowledge base through AI to provide the most accurate answers. It integrates various data sources such as news, social media, research reports, white papers, and on-chain data, allowing users to obtain comprehensive information on a single platform.
Why Develop QnA3?
Web3 is a complex and constantly evolving field, with a large amount of data generated every day, both on-chain and off-chain. However, this data is massive and lacks obvious correlations, making it difficult for most ordinary users to derive valuable insights for their investments and research from the myriad of data sources such as market hot news, on-chain data, discussions on social networks, and various Web3 data platforms.
QnA3 attempts to solve this problem by transforming various data sources in the Web3 field into a large knowledge graph, creating connections between data and allowing users to interact with the AI Agent in natural language, helping them find the most accurate answers.
Users can achieve the following through QnA3:
- Interpret and analyze hot news and events in the market.
- Deeply learn Web3 knowledge; QnA3 will be like a seasoned professor with cutting-edge Web3 knowledge.
- Analyze projects comprehensively, from technology, product, economic models to public opinion.
- Use the most suitable content from different data sources.
Common Use Cases
For different types of users, QnA3 can provide different types of answers.
For Professional Investors
For example, when a professional analyst uses QnA3 to assist in writing an industry research report, explaining and elaborating on complex knowledge requires a lot of effort. QnA3 can help the analyst organize basic materials in seconds.
For Ordinary Web3 Users
Ordinary Web3 users are more concerned about whether they can seize investment opportunities. QnA3 will provide neutral and objective judgments by analyzing news and real-time market data.
For KOLs
KOLs can use QnA3 to build their Twitter content.
How Does QnA3 Work?
QnA3 combines AI's logical capabilities with the team's extensive data capabilities, aggregating multi-source data into a knowledge graph through multi-layer data processing. At the same time, the AI engine automatically analyzes user questions and retrieves the most relevant data from the knowledge graph to generate more precise answers to the questions.
Advantages of QnA3
There are many data and AI products on the market, and QnA3 has certain innovations in various aspects:
Compared to large AI applications like ChatGPT / Claude / Bard, QnA3 has a significant advantage in real-time data and vertical domain knowledge bases. The first three are pre-trained models that cannot respond to events that occur after training, while QnA3 updates its knowledge base in real-time, capable of updating its data on a minute-by-minute basis, providing the most timely information.
Compared to other Web3 AI search engines, QnA3's knowledge graph contains a large amount of structured data, which enables AI to provide more accurate and persuasive answers.
Higher community co-construction level; currently, QnA3 has initiated the MVQ (The most valuable question selection event) and Ridiculous AI activities, aiming to allow ordinary users and expert users from the Web3 community to co-build a knowledge community, creating a more complete Web3 knowledge base.
Conclusion
Imagine a future where Web3 users no longer have to piece together fragmented information from various websites about a hot event, but can use a single dialogue box to understand the conclusions they most want to know. Professional analysts will no longer need to search for materials in various research reports, acting as "research report tailors," but can simply ask questions within their professional knowledge framework and let AI help fill in the "flesh and blood" of their reports.
QnA3 is not just a Web3 knowledge base; it is an infrastructure aimed at constructing a large network from the complex data in the Web3 world. Utilizing large language models and big data technology, QnA3 allows users to reach every corner of the Web3 field within a dialogue box.
In the future, QnA3 will vigorously promote community co-construction, enabling every ordinary user to participate in the construction of this "large network" and gain knowledge and value from it.
With the assistance of AI, QnA3 is creating a "God's Eye" for Web3.
