Is AI trading a true revolution or a false proposition?

When professional traders publicly denounce AI trading as "nonsense," while AI entrepreneurs assert that it is an irreversible future, a soul-searching debate about the truth of AI trading and the cryptocurrency market unfolds intensely in the MyToken community.
Recently, an online AMA hosted by the well-known data platform MyToken deeply explored "The New Landscape of Cryptocurrency: How AI Trading Reshapes Market and Investment Logic." The event invited professional trader Pudate, who has focused on Bitcoin contracts since 2018 and uses self-developed robots. Riconi, the founder of FINWEXai, has been deeply involved in the AI field for eight years and incubated the YOMIRGO project. Ishibashi, a technical expert who serves as CMO of JCrypto Labs and builds computing power optimization models. Additionally, Vincent, the market leader of the Hong Kong blockchain media TechFlame and a practical researcher, and A Chao, a representative of the well-known DEX APEX.

Current Dilemma: Is AI Trading an Illusion or Reality?

When the discussion focused on "the actual stage and market impact of AI trading," the audience quickly divided.
Pudate depicted AI as "unreliable" based on personal experience. He attempted to use AI to assist in writing trading strategy code, only to find that this "advanced assistant" often "cheated and talked nonsense." "The code it generated couldn't even compile, and after correcting the errors, the new version was worse than the old one." In Pudate's view, the current large language models are merely "things that cater to what you say," good at summarizing existing information but unable to produce financial wisdom that surpasses human capabilities.
He posed a soul-searching question: "If AI can really predict the market, then who is losing money? If everyone makes money with AI, is blockchain losing money? Why am I so skeptical?"
A Chao from the skeptical camp also believed that AI trading is currently more in the "Beta testing phase," serving as a testing ground for capital and traders, with hype outweighing actual impact. "At this stage, the influence on market trends is limited, but products that solve the last mile for users will have huge opportunities."
However, the optimistic camp's voices were equally firm and powerful.
Both Riconi and Vincent presented key evidence: the top domestic quantitative institution, Huansquare, significantly outperformed its peers after widely adopting AI algorithms. Riconi even asserted that AI replacing manual trading is "an inevitable trend," as human greed and fear will ultimately be rationalized by technology.
The practical technologist Ishibashi provided a middle-ground perspective. His team invested heavily in self-built computing power, optimizing AI response time from 15 seconds to 7 seconds, training AI to analyze thousands of KOL tweets in real-time. "AI has an absolute efficiency advantage in processing vast amounts of unstructured information." He emphasized that this is not about replacement, but enhancement.

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Essential Dispute: The Logical Differences Between Black Box AI and White Box Quantitative

Regarding "the core differences between AI trading and traditional quantitative trading," the discussion touched on deeper logic.
Pudate first clarified the concepts: Quantitative trading is about building quantifiable and traceable systems; whereas many "AI trading" systems that call upon general large models are opaque "black boxes" in their decision-making processes. True financial AI should be trained and deeply learned in specific fields like "AlphaGo," but he revealed the cruel law of financial markets: truly effective strategies must have confidentiality; once made public, they will fail due to market reflexivity.
Riconi responded to the "black box" concerns from the user's perspective: even traditional funds often present their strategies as black boxes to investors. "Users ultimately care about performance, not the process itself." He believes that if AI can provide better returns, its internal logic is not unacceptable.
Ishibashi's practice points towards integration—allowing AI to handle heavy tasks like signal filtering and review summaries, while humans focus on final decisions and risk control. "AI is an efficiency tool, and humans are the decision-making core."
A Chao, from the user experience perspective, suggested that the key to AI trading lies in "solving the last mile": "Future products should function like personal trading assistants, allowing users to complete the entire process from analysis and decision-making to execution using natural language."

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Survival Guide: How Can Retail Investors Use AI Tools to Hedge Risks and Enhance Efficiency?

For the practical concerns of retail investors, the guests offered pragmatic and cautious advice.
Regarding the entry threshold, Pudate was firm: "You must know how to program, at least understand the principles." He warned that retail investors lacking a technical foundation are most easily harvested by third-party tools that promise "easy profits."
Vincent provided an extremely practical path: boldly try various safe AI trading tools with very small positions (like $100). He shared his experience using a browser plugin that scans front-end pages and automatically executes trades, doubling his funds within a month, emphasizing learning through interaction.
Ishibashi believes that what is most practical for retail investors is to utilize the increasing number of AI signal aggregation products (Signal Panel) in the market for filtering and following. The barrier for independent development is too high.
Riconi forecasted that in the short term, retail investors could obtain AI risk calculation assistance and market prediction services (such as predictions on Federal Reserve interest rate decisions) through B-end products, which will see initial explosive growth.
A Chao predicted from a product evolution perspective: "In the future, more low-threshold AI trading products will emerge, allowing ordinary users to enjoy the efficiency improvements brought by technology."
From the discussion, it was learned that whether it is the data platform MyToken, the well-known DEX APEX, or the teams behind Ishibashi and Riconi, all are developing AI tools to lower the user’s usage and trading thresholds.

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Future Landscape: How Will Cryptocurrency and AI Deeply Integrate?

Looking ahead to the next three to five years, the guests outlined several key integration directions. These directions could truly change the game.
The combination of agents and protocols is receiving significant attention. Vincent mentioned that protocols like ERC-8004, which provide on-chain identity verification for AI agents, are opening up new imaginative spaces—"Your AI financial advisor can automatically compare prices, find the best trading paths, and complete payments."
The AIization of prediction markets is seen by Riconi as a key track in the near term. After analyzing macro data, AI can provide high-probability predictions, and this capability can be directly translated into advantages in prediction markets. "We will see blockbuster products of this kind this year."
The maturity of infrastructure is a prerequisite for popularization. A Chao and Ishibashi foresee that in the future, low-threshold "AI trading agent" frameworks will emerge, allowing users to build their trading robots by combining different modules like building blocks.
"Ultimately, AI will not make everyone a trading genius," Ishibashi concluded, "but it will make rational decision-making and strict discipline more accessible than ever."

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Conclusion

This AMA clearly reveals that the application of AI in the cryptocurrency trading field is not a smooth path, but rather filled with pragmatic explorations and fundamental philosophical debates. It has not yet "reshaped" the market, but is acting as a powerful incremental force, profoundly changing the competitive tools and thinking patterns of market participants in multiple areas, from information processing and efficiency enhancement to strategy generation.
The future belongs to those traders who can effectively use AI to expand their capabilities while maintaining independent judgment. This new landscape of cryptocurrency, initiated by human wisdom and accelerated by machine intelligence, has only just begun.

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Core Insights and Risk Warnings (AI Summary)

1. Development Stage: AI trading is still in the exploratory phase, with limited market impact but rapid development; some institutions have achieved excess returns through AI.
2. Essential Differences: Traditional quantitative trading is a rule-driven white box system, while current AI trading is often a data-driven black box model, with differing logical foundations.
3. Tools, Not "Oracles": The core capability of current general AI is the aggregation, summarization, and induction of information, rather than the "prediction" of the nonexistent. It can be an efficient assistant for researchers but is not a "holy grail" that replaces human judgment.
4. Effectiveness Paradox: The survival premise of continuously effective financial Alpha strategies is confidentiality and limited capacity. Publicly promoted, infinitely replicable "AI printing strategies" are fundamentally questionable.
5. Retail Investor Action Guide: For most retail investors, personally developing AI trading systems is unrealistic. A more feasible path is to use AI for information denoising, strategy backtesting, and discipline execution. Try verified AI trading tools with very small funds to understand their boundaries in practice; maintain critical thinking and be wary of any "guaranteed profit" promises.
6. Future Directions: The integration of agents and protocols, the AIization of prediction markets, and the improvement of infrastructure will become key paths for the combination of AI and cryptocurrency.

The content of this article is based on the AMA transcript, and the views of the guests do not represent the position of MyToken. The cryptocurrency market and AI technology carry high risks, and any tools and strategies mentioned in the text do not constitute investment advice.