Guest Author: Phoebe Peng

Recently, OpenAI released a new tool called Sora that can generate AI videos based on text. Compared to last year's launch of AI search Q&A, text-to-image and other forms, the introduction of Sora represents a significant advancement in AI technology. The debut of this new tool has not only attracted widespread attention in the tech community but also sparked a frenzy in the cryptocurrency market. Many AI-related projects have seen substantial increases, attracting a significant influx of capital.

1. Overview of the AI Track

In 2023, OpenAI’s chatbot product, ChatGPT, with its excellent performance and wide range of application scenarios, quickly became a global focal point in the AI field, igniting an AI craze. This also sparked a bullish trend in the AI track within the cryptocurrency market, with various AI-related projects emerging. This year, OpenAI has launched a new product, Sora, leading people to anticipate whether it can continue the AI wave and bring more innovation and breakthroughs to the industry.

AI (artificial intelligence) is the capability to use computation and machines to mimic human reasoning and problem-solving. With the continual development and application of AI technology alongside the booming cryptocurrency market, the application of AI in the crypto field has gradually become a focal point. 

In the crypto field, the AI theme track covers a range of projects and applications that utilize AI technology to solve problems in cryptocurrency and blockchain.

According to CoinGecko’s data, as of February 22, 2024, the total market capitalization of AI-track tokens has already exceeded $17.4 billion.

2. Applications of AI in the Crypto Domain

As the cryptocurrency market continues to mature and AI technology finds broader applications, the AI-themed crypto project track is showing a trend toward diversification and innovation. Various projects are attempting to implement and promote the application of AI through blockchain technology.

1. Application of Decentralized Computing: Aggregating idle computing resources (CPUs + GPUs) into a market through crowdsourcing computing provides lower-cost computational resources for many tasks, such as pre-training and fine-tuning. Projects like Akash and Render are exploring this area, aiming to address the allocation and utilization of computing resources. However, there are market concerns that crowdsourced computing may not achieve economies of scale, and that most high-performance GPUs aren’t owned by consumers.

2. Trend Toward Decentralized Inference: Running open-source model inferences in a decentralized manner addresses privacy and censorship issues that may arise with centralized services. Projects such as Ritual and Ollama are exploring this area, hoping to provide more secure and private inference services for users.

3. Development of On-Chain AI Agents: Using on-chain applications of machine learning and cryptocurrency payments to address transactions and payments between agents, projects like AI Arena and MyShell are dedicated to exploring this area.

4. Management and Value Capture of Data and Model Sources: Blockchain technology enables autonomous management of data and machine learning models, addressing issues such as data monopolization and fraud. Projects such as Vana and Rainfall are exploring this area, attempting to establish portable data and models to promote their flow and to support the development of personalized networks.

5. Application of Token Incentives: To encourage user engagement and provide a broader market for AI applications through crypto token incentives, projects like MyShell and Deva are exploring this area and attempting to attract user participation. Additionally, incentivizing machine learning operations with crypto tokens can encourage actions such as optimization of weights and fine-tuning, thereby improving model performance and accuracy. Meanwhile, projects like Bittensor and Ritual aim to address issues of quality and accuracy.

6. Importance of On-Chain Verifiability: On-chain model verifiability enhances the composability of models and provides more reliable services for agents. Projects such as Modulus Labs and Upshot.ai are addressing this area as they seek to address the reliability and verifiability issues of agents.

7. Application of Trategy Making and Web3 Searching: ChatGPT-related niche products, such as AI-Powered Investment and Trading Analysis, are capable of conducting detailed analysis and research based on ChatGPT and trading databases. For instance, Bybit has launched TradeGPT, which offers personalized guidance. It utilizes Bybit's comprehensive data repositories to provide actionable intelligence and strategic advice tailored to each user's investment journey. Another example, TypoX aims to become the Google search of Web3 and it will help users to understand everything of the Web3 world.

3. Top 10 Representative Potential Projects in the AI Track

4. Investment Opportunities and Risk Analysis of the AI Track

As an important segment in the crypto domain, the AI track offers rich investment opportunities, along with certain risks.

Investment Opportunities

AI+Crypto Integration Trend: The AI track is a demand-driven segment. It’s believed that in the near future, the integration of AI with cryptocurrencies will become a dominant trend. This integration is expected to enhance development efficiency, audibility and security of smart contracts, and user accessibility. Such integration isn’t limited to the crypto domain, also bringing new enhancements and additions to the experience of on-chain developers and users.

Enormous Demand: AI projects in the crypto domain meet the market's urgent needs for smart contracts, data management and machine learning, etc. As the adoption of cryptocurrencies and blockchain applications continues to expand, the demand for intelligent solutions will keep growing.

Market Potential as the Result of Technological Innovations: These projects utilize innovative AI technologies and blockchain solutions, bringing unprecedented market potential to the crypto domain. For example, the intelligence and audibility of smart contracts will be significantly enhanced, thus improving the security and credibility of blockchain applications.

Support from Well-Known Institutions: Some projects have already received support and funding from renowned institutions and investors, providing strong financial and resource support for project development.

Risk Analysis

Immature Technology: AI technology hasn’t yet matured, and there are still challenges regarding the stability and performance of algorithms. Investors need to carefully evaluate the technological risks involved.

Product Realization: Some projects' technical solutions aren’t fully mature either, so it remains to be seen whether they’re merely hype and concepts, requiring continuous observation and verification.

Data Privacy Issues: AI applications involve a large amount of user data, and the risks of data privacy breaches and misuse still exist.

Project Quality: The AI track is highly competitive, with varying project qualities. Accordingly, there may be instances of low-quality projects attempting to exploit the market, necessitating careful scrutiny of project teams’ capabilities, product functionalities and technical strengths.

5. Outlook on the Development Prospects of the AI Track

The rise of AI in the cryptocurrency domain has brought unprecedented innovation and opportunities to the entire industry. Consequently, many remarkable developments can be expected in the future.

1. Enhanced User Experience and Accessibility: AI technology has brought innovations to the cryptocurrency domain comparable to those of Web 2.0, enhancing everything from infrastructure development to user experience and accessibility. With AI technology, users can engage more easily with the cryptocurrency world, and enjoy more convenient and intelligent services.

2. Significant Improvement in Development Efficiency: Products like OpenAI and Copilot AI are driving improvements in development efficiency that are expected to increase developers' work efficiency by several times. AI-assisted development platforms have already started to play a role in Layer 1 and DeFi applications, which will greatly promote the integration of cryptocurrency with AI technology

3. Enhanced On-Chain Security: The integration of AI not only improves development efficiency but also brings new enhancements to on-chain security. For example, companies such as CUBE3.AI and TestMachine are developing AI integrations for smart contract audits and real-time threat monitoring, which will help enhance the security and stability of on-chain applications.

4. Development in Vertical Domains: The development of technologies such as decentralized computing, ZKML and AI agents will lead to a deep integration of cryptocurrency and AI technology in vertical domains. These areas lay a solid foundation for the future development of cryptocurrency and AI, indicating many exciting innovations and application scenarios to come.

In summary, the AI-themed track in the crypto domain will continue to attract market attention and investment favor, with projects continually growing in aspects such as technological innovation, marketing and team building. With further technological advances and exploration of commercial applications, the integration of cryptocurrency and AI technology will bring about a more intelligent, efficient and secure digital economic ecosystem.

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