Discussion on the Crypto AI Track

Host: Alex, Investment Researcher

Guest: Max, YouTuber; Lydia, a certain internet researcher

Understanding Crypto AI

Alex: Today, let's talk about the highly discussed Crypto AI sector. The first topic is, what are your views on the Crypto AI sector? In your opinion, what business problems is the Crypto AI sector trying to solve? How urgent are these problems?

Max: I think the reason Crypto AI has emerged is to solve two main problems. The first problem is from a cultural perspective, centralized AI itself has some issues that need to be addressed. For example, we may encounter censorship issues and various problems arising from centralization. By incorporating Crypto, Crypto AI has a decentralized effect, allowing for approaches that align more with what the public desires. Another interesting aspect, I believe, is the introduction of incentive mechanisms. The main representative of Crypto is its Token; with this Token, all aspects of decentralized AI can leverage this incentive mechanism to explore more diverse attempts.

Lydia: To be honest, when it comes to business issues, I find this answer not particularly clear for me, especially at the Crypto level. Although there is a popular saying that "AI can improve efficiency, and then Crypto can ensure fairness," if we think carefully, we will find that at this stage, from the perspective of business value, the urgency of improving efficiency is clearly greater than ensuring fairness. The greatest value of Crypto AI at the moment may not be directly reflected in alternative solutions at the current business level, but more in the narrative level. It opens up people's imagination, allowing Crypto and AI—two seemingly unrelated, yet particularly cutting-edge and stylish technologies—to collide in people's minds.

Classification of Projects in the Crypto AI Track

Alex: Based on your understanding of the Crypto AI sector, how would you categorize the projects within this sector?

Lydia: A very common classification method is Crypto empowering AI or AI empowering Crypto, which are two major approaches. Currently, what we see more is AI empowering Crypto, meaning that Crypto projects are trying to add some AI attributes. If Crypto empowers AI, the ceiling is indeed higher, but it is more difficult to achieve and prove, requiring more time.

Max: I primarily divide it into three different tracks. The three tracks are the architecture layer, resource layer, and application layer. The architecture layer is somewhat like a foundational framework, on which you can develop different AI projects. The resource layer consists of various resources needed for AI development built on this architecture layer, such as computing power, data, models, etc. The application layer is closer to user usage, such as AI agents.

Opportunities and Challenges of Crypto AI

Alex: What do you think is the main challenge currently facing Crypto AI? What kind of industry or narrative opportunities do you see for Crypto AI in the next one to two years?

Max: The main challenge is that Crypto AI is still in its early stages. Currently, most of the market capitalization has risen significantly, which is likely more due to speculation. I believe we really need to find Product Market Fit or discover some applications that can genuinely be used; there are still relatively few applications that can develop these. In terms of industry and narrative opportunities, I think we are at a very good point in time, like Bitcoin just breaking 100,000, and everyone's attention on Crypto has shifted to the cryptocurrency circle. With the softening of U.S. regulatory policies, we will have more opportunities, time, and resources to try different things.

Lydia: I think we might be approaching the peak period of the technology maturity curve as described by Gartner. Right now, the market is very FOMO-driven, with a huge explosion on the supply side, but it's a mixed bag phase. In terms of challenges, I think there might be a mismatch between market sentiment and technological progress. As for future opportunities, from an industry perspective, I believe we can look back at Max's framework to examine the costs and demands of these sectors. For example, we all know that the three main components of AI development are computing power, data, and algorithms. The main demand comes from whether they can significantly reduce the cost for users to access the same resources.

Crypto AI Projects Worth Paying Attention To

Alex: If you had to choose one or two AI projects among those you are currently aware of that are most worth paying attention to, which ones would you recommend? Please explain your reasons for the recommendations and the potential risks you think this project might face.

Lydia: I recommend Bittensor. First of all, the team's narrative ability is top-notch. Secondly, the institutional adoption rate is high, such as Grayscale's support for it. Thirdly, this project has experienced large-scale FUD, but has demonstrated vitality. Potential risks may include its token economic model and degree of decentralization.

Max: I am also most concerned about Bittensor. Its advantages lie in its incentive mechanism design and the development of open-source models. In terms of risks, its current token issuance rate is very high, which may lead to value dilution. Additionally, although its goal is decentralization, the mainnet is still controlled by the team at present. Besides Bittensor, I also recommend paying attention to Vana (decentralized data), Arweave (AI computer), and Nier (chain abstraction).

Evaluation Strategies for Crypto AI Projects

Alex: If we were to abstract these ways of thinking, what dimensions are you most concerned about when researching and selecting Crypto AI projects? In other words, what are the core factors you consider when deciding whether to invest in a project?

Max: I mainly focus on five aspects: team, product, profitability, future outlook, and token economic model. Among these, I place the most importance on the team, including the background of the founders, investors, and the quality of the community.

Lydia: I also value the team highly, especially their storytelling ability and execution power. In addition, I will pay attention to the token design of the project and the overall brand culture. A good Crypto AI project should be able to highlight its uniqueness.

Alex: I will consider the market cycle of the project to determine whether it is in a phase of short-term over-optimism or long-term over-pessimism. For tracks with clear commercial value, the best investment timing is often when the market is overly pessimistic about its long-term prospects.

Commonly Used AI Tools Sharing

Alex: What AI tools do you use in your daily life or work? How do you generally use them, and what role do they play?

Lydia: I mainly use three tools: GPT (for English practice and psychological counseling), perplexity (for search and knowledge summarization), and Doubao (for YouTube video summarization).

Max: I am a heavy user of ChatGPT, mainly for knowledge absorption and organization, as well as image generation. I am researching how to input my investment research framework into AI to generate more personalized research reports.

Alex: I also often use GPT, mainly for article formatting and deep learning. Perplexity has become my preferred search tool, replacing traditional search engines. I believe that future searches will be driven more by AI, which will bring about a significant increase in productivity.