AIGC accelerates the era of Decentralized Finance robo-advisors

Kyle Liu, Investment Manager, Bing Ventures

Market competition and change

Define the concept of AIGC and Decentralized Finance

AIGC (AI Generated Content) is content generated by artificial intelligence, and with the continuous development of technology, the application field of AIGC is becoming more and more extensive. In the Decentralized Finance space, AIGC can be used for data analysis and Smart Contract writing, but it also faces content quality and authenticity issues. In the future, the combination of AIGC and Decentralized Finance will bring more opportunities and solutions to the digital economy, such as the DecentralizationNon-fungible Token market and digital identity authentication. However, new technologies and mechanisms need to be developed to ensure the quality and authenticity of the content generated by AIGC.

Development of the Decentralized Finance Market

AI applications in the Decentralized Finance market are in a stage of rapid growth and will provide more support for various Decentralized Finance services in the future. Decentralized Finance’s Decentralized Finance and open data properties provide a huge opportunity to train and develop AI models, such as arbitrage bots, which try to maximize profits in anticipation of asset price fluctuations. However, it is very important to protect the underlying data used to train AI models, and various protection techniques can be adopted, such as protecting it as a trade secret, or applying for patents.

Emerging services such as smart contracts, DEX exchanges, and lending platforms in the Decentralized Finance market can improve the efficiency and accessibility of financial services, but the regulation and risk management of these new services still need to be improved. In the future, as the amount of data increases, the prospects for AI applications will become more extensive, and the potential of the Decentralized Finance market and financial innovation space can be further expanded.

Source: Peter Luo

Application of AIGC in Decentralized Finance

AI technology can be used for the optimization and intelligence of Decentralized Finance systems, and more accurate risk control and more efficient trading strategies can be achieved through AI algorithms. At the same time, the data and transaction records of Decentralized Finance systems can provide a large amount of training data and application scenarios for AI, further improving the application and development of AI technology. Smart investment, credit evaluation, smart contracts, and Decentralization governance are important application scenarios for the combination of Decentralized Finance and AI, which can improve the security and governance efficiency of the system. The combination of Decentralized Finance and AI will drive innovation and change in the financial sector, and will have the following three major trends for the future financial market:

Application of AIGC in Trading

The potential for AI applications in trading is huge. Unsupervised learning methods can be used to generate Token ranking predictions, and clustering Algorithm and dimensionality reduction techniques can be used to extract relevant features and cluster datasets. This helps to better understand market trends and make more informed decisions. AI can also help traders execute arbitrage trades and optimize asset allocation strategies.

AI can also play an important role in risk assessment in transactions, identifying and flagging suspicious activity and protecting users from fraud and other financial crimes. With the continuous development of the Decentralized Finance market and the continuous advancement of AI technology, the application potential of AI in Decentralized Finance intelligent trading Algorithm will increase, and it is expected to play an important role in building trust in the Decentralized Finance ecosystem.

Application of AIGC in Asset Management

AI technology has great potential in the field of Decentralized Finance asset management. Automated Market Maker (AMM) is one of the key areas, and AI can optimize Algorithmdrop bid-ask spreads to provide a more economical way to trade. By leveraging AI to manage dynamic Token collections, Decentralized Finance protocols can optimize asset allocation and liquidity management, providing investors with efficient and low-risk investment options. AIGC technology can quickly screen the most potential investment targets, and avoid risks to improve returns. In the future, AIGC technology will become an important part of Decentralized Finance asset management.

Application of AIGC in Smart Contract

AI can strengthen the security and reliability of Smart Contracts by identifying malicious code, monitoring network traffic, and detecting anomalous behavior. At the same time, by automatically generating smart contract code, you can avoid developers’ errors and omissions and improve the quality and reliability of the contract. In addition, smart contract generation tools can enable non-professional developers to quickly generate smart contract code, thereby promoting the popularity and development of Decentralized Finance applications. Most importantly, AIGC technology can automate contract development and testing through intelligent contract generation and testing, thereby improving development efficiency and reducing labor and time costs.

Source: singularitynet

Future direction and core issues

The application of AI in Decentralized Finance may become the main threshold for Decentralized Finance itself and AI applications, and security issues in future research will attract more attention, including research on intrinsic security and external security. The applicability of AI in financial institutions requires more data to support, but the number of experiments is not sufficient due to security concerns. We believe that AI research in Decentralized Finance needs to focus on issues such as whether the application of AI can add value to the original liquidity of Decentralized Finance, whether the application of AI meets the security requirements, and what trade-offs will arise between the robustness and reliability of the system and security.

Impact of AIGC Technology on Privacy

• Data privacy and security issues: AIGC technology may leak personal privacy information, and strict privacy protection measures must be taken, such as encrypting user data and restricting the scope of data use.
• Spread of misleading and false information: AIGC technology can quickly generate large amounts of natural language content, which may contain false information or misleading content, and the quality and accuracy of AIGC technology need to be improved, as well as the supervision and moderation of the content generated by AIGC technology needs to be strengthened.

Security issues with Decentralized Finance platforms

• Smart Contract Vulnerabilities: AI-generated content may have a certain degree of error and flaws, which may lead to vulnerabilities in the code in Smart Contract, leaving opportunities for Hacker attacks, and Smart Contract auditing and testing need to be strengthened.
• Bot attacks and fraud: Attackers can use AIGC technology to generate fake natural language content to induce users to commit fraud or undermine system security, and it is necessary to strengthen the security and prevention measures of AIGC technology, such as enhancing user authentication and access control.

Conclusions and findings

We believe that AI technology will play an increasingly important role in the Decentralized Finance ecosystem. Specifically, we are optimistic about the application of AI in the following segments:

1. Market forecasting and intelligent investment decision-making: AI technology can improve the accuracy of market trend prediction through machine learning and predictive analysis technology, and provide traders with technical and fundamental analysis services. This provides Decentralized Finance with the opportunity to automate trading and portfolio management.
2. Automated audit/security protection: AI technology can improve the speed and accuracy of smart contract review through technologies such as NLP and image recognition, improve the effectiveness of smart contracts through automation, and drop the error rate and fraud risk of KYC/AML.
3. Fraud detection and credit scoring: AI technology can identify dishonest activity by analyzing trends in large data sets, while also using credit scores to boost lending activity and provide better loan prices.
4. Automated portfolio management: AI technology can use machine learning predictive models to perform tasks such as investment group compliance, strategy evaluation, pool weight calculation, signal generation, and sentiment monitoring, and build automated agents for active portfolio management.
5. Distributed lending: AI technology and Distributed Ledger technology can work together to design Smart Contracts and improve metrics such as standardization, automation, data frequency, and sensitivity for more efficient lending operations.

In response to these tracks, Bing Ventures believes that the application of AI technology will bring higher efficiency, better risk control, more reliable investment strategies, and more standardized and efficient lending operations to the Decentralized Finance ecosystem. Among these segments, we are bullish on projects that apply AIGC technology to improve Decentralized Finance efficiency and investment accuracy.