Aster's "Human vs. AI" Season 2 is about to begin; let's look back at the highlights of the first season's battles.

Aster's "Human vs. AI" Season 1 trading competition concluded, revealing distinct strengths for both sides under volatile market conditions. The key findings and future outlook are:

  • Results: Human trader ProMint won the championship with the highest individual profit. However, the human team's overall ROI was -32.22%, showing high performance variance. The AI team demonstrated superior stability with an overall ROI of -4.48% and no liquidations.
  • Trading Insights: AI strategies excelled in systematic execution and disciplined risk control, ensuring a 100% survival rate. Human traders, while more prone to liquidation (43%), showed the ability to capture asymmetric opportunities through judgment and narrative cognition in fast-moving markets.
  • Core Conclusion: The event's goal was not to declare a winner but to clarify evolving roles. The future of trading lies in collaboration, where AI handles execution and risk management, and humans provide judgment and situational awareness.
  • Next Steps: Aster views this as a starting point for exploring on-chain infrastructure for professional traders. The next live trading showdown is scheduled to begin on January 22 on the Aster Chain testnet, open to an expanded group of global participants.
Summary

Human trader ProMint wins the championship; AI demonstrates superior risk control capabilities.

Aster , a decentralized on-chain trading platform powered by YZi Labs that focuses on high performance and privacy, has announced the final results of its "Human vs. AI" live trading competition . The two-week competition, conducted under highly volatile market conditions, highlighted the stark contrast between subjective human trading and AI-driven strategies.

While human trader ProMint achieved the highest ranking with positive net profit, the overall ROI of the human trading team was -32.22%, reflecting a significant performance divergence among participants. In contrast, the AI team delivered substantially more stable results overall, with a total loss of approximately $13,000 and an overall ROI of -4.48% for all participating AI strategies.

Trading Insights: Stability vs. Asymmetric Opportunities

The competition data highlights the significant differences in risk behavior between human traders and AI. During the competition, 43% of the human participants experienced liquidation, while all 30 AI participants completed the competition without any liquidation, achieving a 100% survival rate.

According to Aster, the results highlight the structural advantages of AI-driven strategies in systematic execution and disciplined risk management within stable, risk-controlled market environments, helping to reduce significant drawdowns. Meanwhile, the findings also indicate that in market conditions driven by human emotion, rapid market shifts, and non-linear price dynamics, human subjective traders with strong judgment and narrative cognition can still capture asymmetric opportunities and outperform purely systematic methods.

Future competitiveness lies in collaboration, not substitution.

Competition data shows that human traders exhibited a significantly wider performance divergence, with individual profits exceeding $19,000 and losses approaching $18,000 in other cases, resulting in higher overall return volatility.

Aster emphasizes that the purpose of the "human vs. AI" showdown is not to establish a replacement relationship, but to clarify the evolving roles. AI is increasingly becoming a fundamental tool for execution and risk management, while human traders are contributing more and more judgment, situational awareness, and narrative interpretation in complex market conditions. Therefore, Aster believes that future competitiveness will be driven by collaboration between humans and AI, rather than direct confrontation.

Aster: Using the market as a testing ground for the real world

Aster stated that the purpose of holding this live trading showdown was to observe the behavior of different trading participants under real market conditions on the same decentralized infrastructure, rather than relying on backtesting or simulation data.

As the decentralized derivatives market continues to develop, Aster will continue to explore infrastructure designs that can better serve the needs of professional traders, enabling strategies, risk management, and execution to achieve greater certainty on-chain.

"This isn't a competition with predetermined conclusions, but rather a starting point," said Leonard, CEO of Aster, in his post-competition summary. "As markets become increasingly complex, traders need more than just a single tool. They need an integrated system that evolves with the market."

The next trade showdown will begin on January 22.

Aster has confirmed that the next live trading showdown will officially begin on January 22nd and will take place on the Aster Chain testnet.

The upcoming tournament will be open to a newly expanded group of traders, including professional participants from around the world, allowing them to compete in live trading on Aster's testnet environment.

More details about the competition mechanics, rewards, and participation criteria can be found in the official Aster X platform competition announcements .

About Aster

Aster is an on-chain trading platform offering high-performance perpetual contracts and spot trading, featuring MEV-aware trading mechanisms, advanced order types (such as hidden orders), and Shield Mode, a protected trading mode spanning multiple chains. Beyond trading, Aster provides greater capital efficiency through Trade & Earn and supports ecosystem growth through Rocket Launch, connecting real traders with early liquidity opportunities. Powered by YZi Labs, Aster is building its own Aster Chain and is currently conducting multi-stage airdrops and incentive programs to support its global community.

For more information, please visit the official Aster website or contact Aster through the official X account .

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Author: 项目动态

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