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veDAO Research Institute: How does AI affect Web3?
In the context of "AI", the only certainty is uncertain. People like certain things, but the uncertainty brought about by "AI" is irreversible under the tide of technological development. Optimists believe that the emergence of "AI" will bring unimaginable help to the whole world in reducing costs and increasing efficiency. The pessimists believe that "AI" will have a profound impact on the rules of the game in the current industry, and therefore will bring a lot of unemployment.
But in any case, from the appearance of "ChatGPT" to the present, people's views on "AI" have gradually accepted from surprise and worry. People seem to realize that whether they welcome it or reject it, AI will undoubtedly go deep into various fields of people and bring about disruptions to various industries with its own mechanism and potential.
Now, AI; begins to enter Web3 and has an impact on the entire industry.
OneKey; former founder Wang Yishi tweeted: The narrative of Web3 has shifted from cryptocurrency to AI. Wang Yishi's point of view is not an isolated case. Many people in the Web3 industry believe that AI; has a huge impact on Web3, especially the emergence of the concepts of "NFT" and "GameFi" domains, AIGC; There is a whole new paradigm. From; PGC (Professionally Generated Content, professionally produced content) to; UGC (User Generated Content; user generated content), and now; AIGC, the work of content creation is handed over to the program.
In addition to the impact of "AIGC" on Web3 content, in fact, AI; has a far-reaching impact on Web3 than we imagined.
AI; is "rectifying" Web3
AI; The "rectification" of Web3 comes from two aspects: On the one hand, the emergence of AI; technology has distracted capital from Web3.
Before the emergence of "AI", Web3 once became a favorite in the eyes of "VC" and institutions, and all walks of life also launched various Web3 concepts (such as digital collections, metaverses) as gimmicks. But after the emergence of "AI", this situation has changed.
In the eyes of institutions, AIGC; at least looks more reliable than Web3, at least it is a practical thing, not a concept that needs to be foreseen. Institutional interest is shifting, plus bear markets and regulation for other reasons. According to the statistics of the Gyro Research Institute, the "3" global financing event in the Web3 field this year occurred;
Funding, is leaving the Web3 space and going in; AI.
Another aspect of "rectification" is: the emergence of AI; the mechanism and logic of the Web3 domain are changing. The Web3 project began to focus on adding elements of "AI" to its own ecology. Part of the project began to evolve at least with "AI" concept or at least with "GPT" interface to get it out. We can regard this phenomenon as the "rectification" of the Web3 world by AI; it can also be regarded as a self-response method based on the "AI" strong "invasion" of the Web3 world.
So there is the emergence of the concept of AI Web3. In the integration process of "AI" and Web3, many different products have emerged on the market, which can be roughly divided into two categories: one is based on the direction of the project itself, adding "AI" elements. This type of product often involves some "AI" tool interfaces on the basis of its own products, and when "PRing" externally, it emphasizes "AI" on the empowerment and promotion of products. For example; AIGOGE.
Another combination of AI+Web3 is to do it with the idea of reducing costs and increasing efficiency, focusing on; AI+ trading strategy; Pionex; focusing on; AI+ infrastructure construction; Getch, Cortex, SingularityNET; focusing on; AI+ financial forecasting The; Numerai; etc.
The emergence of Web3 products with different "AI" concepts reflects the market and capital's favor for this type of product, such as "AIDOGE" currency; 2; days rose; 218.50%; launched on April; 18;. (Fetch.ai) FET, SingularityNET (AGIX), Ocean Protocol (Ocean) and other project tokens increased by ;110%;,;61.53%;,;66.67%; in ;90; days respectively.
While the secondary market for AI Web3 concept is booming, the performance of the primary market is even more gratifying. Since the beginning of this year, AI Web3 concept products have also received financing one after another. On March 29 this year, Fetch.ai; received an investment of $40 million from SWF Labs.
At present, the concept of AI+Web3 seems to become a major trend in the future, so here, veDAO; Research Institute sorted out; AI; may sort out the different tracks that Web3 will bring about change, for reference .
AI; Empowering different tracks of Web3
Based on;AI;trading strategy
The general idea of the liquidity mining strategy based on "ChatGPT" is to use the "ChatGPT" model to predict market conditions to decide whether to participate in liquidity mining and choose the best time.
AI; the role it brings to trading strategies:
Based on; AI; sentiment analysis strategy
The strategy is based on the natural language processing capabilities of ChatGPT, which conducts sentiment analysis on market sentiment by analyzing text data such as news reports and social media posts. A trading strategy may choose to buy when the sentiment in the majority of the text is "positive" or "buy"; and vice versa.
The realization of this strategy requires the collection of market-related text data, and the cleaning, analysis and modeling of these data. For the modeling of the sentiment analysis model, a supervised learning algorithm can be used to train the labeled training data to predict the emotional tendency of the text. The formulation of trading strategies can be adjusted according to the prediction results of the model, combined with market trends and other factors.
Analysis of trading strategies based on "AI"
The strategy is based on; ChatGPT; the ability to understand the text description of the trading strategy, and analyze and evaluate the trading strategy. For example, analyze the backtest results and historical returns of trading strategies to evaluate the effectiveness and reliability of the strategies, and formulate trading strategies accordingly. For the analysis and evaluation of trading strategies, machine learning algorithms can be used to predict the rate of return and risk of strategies through model training and optimization. The formulation of trading strategies can be adjusted according to the prediction results of the model, combined with factors such as trial production trends.
AI-based asset portfolio management
Asset portfolio management tools based on "ChatGPT" can use natural language processing technology to help users better manage asset portfolios, optimize asset allocation and risk control, and provide more accurate forecasts and suggestions in investment decision-making. can do:
Automated asset analysis and currency selection: Use the natural language processing of "ChatGPT" to analyze and evaluate the fundamentals, market conditions, and macroeconomic factors of various assets, so as to automatically select suitable investment targets and reduce the risk of wrong decisions.
Asset portfolio optimization: Through; ChatGPT; predict market trends and risks, provide users with asset portfolio optimization suggestions to achieve risk diversification and return maximization.
Automated transaction execution: Based on the "ChatGPT" transaction decision-making model, the automatic execution of buying and selling transactions realizes real-time adjustment and optimization of assets while reducing the risk of human intervention.
Based on; AI; simulated trading tool (AI Demo Account)
The simulated cryptocurrency trading tool based on "AI" is a virtual trading platform based on the "AI" algorithm, simulating the real cryptocurrency market environment, and providing virtual funds for users to conduct simulated transactions. Users can learn cryptocurrency transactions on the platform, formulate trading strategies and conduct simulated transactions without taking risks in real transactions, allowing more users to experience the "AI" function while also realizing the advancement of self-investment level.
DEX+AI; Feasible directions:
Auxiliary decision-making: analysis and mining of trading data, providing more accurate and comprehensive market analysis and forecasting, and helping traders make more informed investment decisions.
AI; Security:
Improving transaction speed and efficiency: Optimizing the transaction process (such as the best routing selection) through "AI" technology can reduce transaction congestion, reduce transaction costs, and accelerate transaction completion time.
Solve the current; DEX; several major problems:
Summarize:
Generally speaking, the emergence of AI; is not just a simple new technology, but a new concept and new field, which will bring a series of iterations and even subversions to the underlying operating logic of the entire society. The same is true for the Web3 world. The relationship between "AI" and Web3 will not be limited to the integration of concepts, or the simple addition of "AI" tools to a certain project. Instead, go directly to the underlying logic of Web3, so that all behaviors in Web3 are endowed with the meaning of "AI", making Web3 more efficient and smarter.
Just like the philosophical connection between production tools and production relations. The two cannot be viewed independently. What kind of production tools have what kind of productivity, and what kind of productivity has provided the necessary conditions for the emergence and popularization of corresponding production relations. If Web3 with the blockchain as the bottom layer represents a newer production relationship, then "AI" is undoubtedly the most advanced production tool of this era. Therefore, we have reason to believe that the emergence, popularization and integration of "AI" technology as a production tool is bound to play a decisive role in the popularization and promotion of the Web3 concept.
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