If there can only be one keyword for 2025, I would choose “AI Agent.” On January 6, OpenAI CEO Sam Altman stated that he is confident in having found the path to building AGI (Artificial General Intelligence), predicting that in 2025, the first AI agents may “join the workforce” and fundamentally transform business productivity. In my opinion, this is not mere sensationalism but rather a new chapter in AI development.

The Emergence and Evolution of AI Agents

In the past six months, with the rapid advancement of artificial intelligence and blockchain technology, AI Agents have become a hot sector in the crypto industry. These autonomous entities, developed using AI technology, can simulate human cognition and decision-making processes, demonstrating high levels of intelligence and adaptability in perception, analysis, and action. Although current AI Agents still lag far behind humans in general intelligence, their emergence is poised to redefine the relationship between humans and technology.

Current large models (such as ChatGPT) excel in language processing and content generation but face significant limitations in application. The core design of large models is rooted in generating probabilistically optimal responses based on massive data training. This makes them powerful “language engines” capable of answering questions and providing suggestions but unable to make and execute decisions autonomously. For instance, in complex enterprise management or emergency response scenarios, large models typically remain as “advisors,” whereas AI Agents can quickly formulate and implement plans by combining preset goals with dynamic environmental inputs.

In healthcare, large models can recommend potential treatments based on user-described symptoms. However, in sudden emergencies such as cardiac arrest, a large model cannot, like an AI Agent, analyze sensor data to assess a patient’s condition and immediately control medical equipment to perform cardiopulmonary resuscitation.

In contrast, AI Agents surpass the scope of current large models by moving beyond “data processing” to complete the full loop from “perception” to “action.” For example, in autonomous driving, AI Agents can analyze road conditions in real-time, integrate traffic regulations and vehicle status, determine the optimal driving route, and dynamically adjust driving strategies. In the financial sector, AI Agents can monitor global market information in real-time and dynamically rebalance portfolios to maximize returns.

AI Agent’s Code of Conduct: Smart Contracts

When AI Agents become active in the scenarios mentioned earlier, they could be referred to as “AI Beings,” a new species created by humans, powered by computing resources. This raises a crucial question: what should define the behavioral guidelines of such powerful entities? My answer is “smart contracts.”

As the backbone of cryptocurrencies, smart contracts are essentially agreements expressed in code. Enabled by blockchain technology, they possess the following characteristics:

• Decentralization: Free from traditional institutional constraints.
• Immutability: Ensuring the authenticity of transactions and records.
• Traceability: Providing transparent information flow for all participants.

Unlike traditional contracts, smart contracts require no intermediaries for execution, relying solely on pre-coded rules. This enhances efficiency and significantly reduces the risk of human interference and potential mismanagement.

If computing power is the blood of AI, smart contracts are its soul.

AI Agents need to follow established rules and ethical guidelines when performing tasks. Smart contracts offer a natural solution for this in the context of cryptocurrencies. For instance, in a decentralized logistics network, AI Agents can automatically manage transport scheduling and fee settlements based on blockchain records, ensuring transparency in resource allocation and transactions.

Imagine a decentralized education platform centered on cryptocurrency. AI Agents could help students create personalized learning plans and distribute crypto rewards based on learning outcomes, encouraging continuous study. All records of students’ achievements, progress, and rewards would be recorded on-chain, eliminating biases and human interference inherent in traditional educational systems.

The integration of AI Agents with crypto also offers the compelling advantage of seamlessly incorporating game theory.

Game theory, at its core, is the science of decision-making, studying strategic choices and equilibriums among competing interests. The cryptocurrency ecosystem is an ideal playground for game theory. The interactions among miners, investors, and developers are multi-party games, while blockchain protocols steer behaviors through mechanism design. In Bitcoin’s network, for instance, miners compete with computing power for rewards, while the protocol’s rules ensure security and decentralization.

Combining AI Agents with crypto can further enhance decision-making and collaboration efficiency. In future smart cities, AI Agents could be employed in resource allocation and traffic management. Using cryptocurrency incentives and game theory models, they could optimize solutions across various objectives:

• In energy management, AI Agents could negotiate priority and cost allocation for energy use, maintaining a supply-demand balance.
• In international trade, AI Agents could use cryptocurrencies and smart contracts to settle transactions in real-time, avoiding delays and high fees associated with traditional banking systems.

Consider a future complex AI Agent system named “Jarvis.” As a “digital assistant,” it could coordinate multi-level collaborations among individuals, businesses, and governments. “Jarvis” would operate within a transparent and dynamically adjustable crypto-based economy, where users earn rewards by contributing data or services, and “Jarvis” purchases necessary resources using cryptocurrencies, creating a closed-loop economy.

The rise of AI Agents and the widespread adoption of cryptocurrencies will jointly drive a new era of collaboration:

• Collaboration between humans and AI: AI Agents serve as intelligent assistants for individuals and businesses, handling tedious tasks so humans can focus on creative work.
• Collaboration among humans: Cryptocurrencies ensure fairness and transparency in cooperation, incentivizing greater participation.
• Collaboration among AI: AI Agents share resources and knowledge through cryptocurrencies, achieving more efficient collaboration.

Potential Risks of AI Agent + Crypto

On one hand, while the integration of cryptocurrencies and AI Agents is theoretically feasible, its technical implementation faces numerous challenges, such as:

• Security Issues: Although blockchain technology emphasizes decentralization and immutability, vulnerabilities in smart contracts could be exploited maliciously, leading to financial losses or system failures.
• Scalability Challenges: Current mainstream blockchains (such as Ethereum) have limited performance when handling large-scale transactions and smart contract executions, potentially becoming a bottleneck for widespread AI Agent applications.

On the other hand, once the behavioral rules of AI Agents are solidified through cryptocurrency smart contracts, they may lack flexibility, making it difficult to address complex ethical problems, including:

• Responsibility Attribution: If an AI Agent causes losses due to smart contract execution, should the responsibility lie with the AI Agent’s developer, the smart contract designer, or the user?
• Privacy Issues: AI Agents need to process large amounts of data in real-time, raising concerns about how this data is stored, used, and shared, which could lead to serious privacy disputes.

Furthermore, the introduction of cryptocurrencies might deepen economic disparities. When combined with AI Agents, those with technological advantages may further consolidate their dominance in economic activities. Individuals and small businesses excluded from the wave of AI and cryptocurrency technologies may be marginalized due to the inability to afford the technological costs, exacerbating social inequality.

The convergence of AI Agents and cryptocurrencies represents the early stage of a technological revolution. Its potential lies in enhancing efficiency and fairness through rule-based automation, driving changes in collaborative models. However, this combination is not a perfect solution. Its complexity and risks require cautious consideration in both technological development and societal application. While we should actively explore its value, we must also remain vigilant about the inequality and uncertainties that technology could bring.

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