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加密貨幣新聞文章

什麼是人工智慧代理?它們與 Telegram 交易機器人有何不同?

2024/12/31 21:42

自今年下半年以來,人工智慧代理的話題不斷受到關注。最初,真相的AI聊天機器人終端因其在X上的幽默帖子和回复(類似於微博上的“羅伯特”)而引起廣泛關注,並獲得了a16z創始人馬克·安德森(Marc Andreessen)的5萬美元資助。

什麼是人工智慧代理?它們與 Telegram 交易機器人有何不同?

AI Agents, a hot topic in the Web3 community, have sparked discussions and debates. But what exactly are AI Agents? How do they differ from Telegram trading bots? And why do they face skepticism despite their potential benefits?

AI Agents作為Web3社群的熱門話題,引發了討論和爭論。但人工智慧代理到底是什麼?它們與 Telegram 交易機器人有何不同?儘管它們有潛在的好處,為什麼它們仍面臨懷疑?

AI Agents are intelligent agent systems powered by large language models (LLMs) that can perceive their surroundings, make logical decisions, and complete complex tasks by utilizing tools or executing actions. Their workflow involves:

AI 代理是由大型語言模型 (LLM) 提供支援的智慧代理系統,可以感知周圍環境,做出邏輯決策,並透過利用工具或執行操作來完成複雜的任務。他們的工作流程包括:

* Perception module (acquiring input)

* 感知模組(獲取輸入)

* LLM (understanding, reasoning, and planning)

* LLM(理解、推理與規劃)

* Tool invocation (task execution)

* 工具呼叫(任務執行)

* Feedback and optimization (validating and adjusting)

* 回饋和最佳化(驗證和調整)

For example, in the context of Web3 applications, AI Agents differ from Telegram trading bots or automation scripts in the following way:

例如,在 Web3 應用程式的上下文中,AI 代理程式與 Telegram 交易機器人或自動化腳本的不同之處如下:

Suppose users want to execute arbitrage trades when profits exceed 1%. In a Telegram trading bot that supports arbitrage, users can set a trading strategy for profits greater than 1%, and the bot will begin executing trades that meet this condition. However, these bots lack the ability to assess risk and will continue executing arbitrage trades as long as the profit condition is met. In contrast, AI Agents can automatically adjust their strategies. For instance, if a trade's profit exceeds 1%, but data analysis reveals that the risk is too high due to potential sudden market changes that could lead to losses, the AI Agent will decide not to execute the arbitrage trade.

假設用戶想要在利潤超過1%時執行套利交易。在支援套利的 Telegram 交易機器人中,用戶可以設定利潤大於 1% 的交易策略,機器人將開始執行滿足此條件的交易。然而,這些機器人缺乏評估風險的能力,只要滿足獲利條件就會繼續執行套利交易。相比之下,人工智慧代理可以自動調整策略。例如,如果一筆交易的利潤超過1%,但數據分析顯示由於潛在的市場突然變化可能導致損失,風險過高,AI Agent將決定不執行套利交易。

Thus, AI Agents possess self-adaptability, with their core advantage being the ability to self-learn and make autonomous decisions. Through interaction with the environment (such as market conditions, user behavior, etc.), they adjust their behavioral strategies based on feedback signals, continuously improving the effectiveness of task execution. They can also make real-time decisions based on external data and continuously optimize decision-making strategies through reinforcement learning.

因此,AI Agent具有適應性能力,其核心優勢是自我學習和自主決策的能力。他們透過與環境(如市場狀況、使用者行為等)的交互,根據回饋訊號調整自己的行為策略,不斷提高任務執行的有效性。他們還可以根據外部數據做出即時決策,並透過強化學習不斷優化決策策略。

While AI Agents sound advanced and capable of enhancing user experiences, they also face skepticism in the community. This is mainly because AI Agents are still just tools and cannot complete entire workflows independently. They can only enhance efficiency and save time at certain nodes. Moreover, at the current stage of development, the role of AI Agents is mostly concentrated on helping users issue MeMes and manage social media accounts. As a result, the community戲稱" , poking fun at the fact that assets ultimately belong to the developer, while liabilities are assigned to the AI.

雖然人工智慧代理聽起來很先進並且能夠增強用戶體驗,但它們也面臨社群的質疑。這主要是因為AI Agent仍然只是工具,無法獨立完成整個工作流程。它們只能在某些節點提高效率並節省時間。而且,在目前的發展階段,AI Agent的角色大多集中在幫助用戶發布MeMe和管理社群媒體帳號。於是,社區戲稱「資產最終屬於開發者,負債則歸AI所有」。

However, just this week, a new application of AI Agents emerged with the launch of an AI Agent for token presale by aiPool. This AI Agent leverages TEE technology to achieve trustlessness. The wallet private key of this AI Agent is dynamically generated in a TEE environment, ensuring security. Users can send funds (such as SOL) to the wallet controlled by the AI Agent, which then creates tokens according to set rules and launches a liquidity pool on a DEX, while distributing tokens to eligible investors. The entire process does not rely on any third-party intermediaries and is fully completed autonomously by the AI Agent in a TEE environment, avoiding the common rug pull risks in DeFi. It is evident that AI Agents are gradually evolving. I believe that AI Agents can help users lower barriers and enhance experiences, and even simplifying part of the asset issuance process is meaningful. However, from a macro Web3 perspective, AI Agents, as off-chain products, currently serve merely as auxiliary tools for smart contracts, so there is no need to overstate their capabilities. Given that there has been a lack of significant wealth effect narratives aside from MeMe in the second half of this year, it is normal for the hype around AI Agents to revolve around MeMe. Relying solely on MeMe cannot sustain long-term value, so if AI Agents can bring more innovative gameplay to trading processes and provide tangible value, they may develop into a common infra tool.

然而就在本週,隨著aiPool推出用於代幣預售的AI Agent,AI Agent的新應用程式出現了。此AI Agent利用TEE技術實現去信任化。該AI Agent的錢包私鑰是在TEE環境中動態產生的,保證了安全性。用戶可以將資金(例如SOL)發送到AI代理控制的錢包,然後AI代理根據設定的規則創建代幣,並在DEX上啟動流動性池,同時將代幣分配給符合條件的投資者。整個過程不依賴任何第三方中介,完全由AI Agent在TEE環境下自主完成,避免了DeFi中常見的拉扯風險。很明顯,人工智慧代理正在逐漸發展。我相信AI Agent可以幫助使用者降低門檻、提升體驗,甚至簡化部分資產發行流程也是有意義的。但從宏觀的Web3角度來看,AI Agent作為鏈下產品,目前僅作為智能合約的輔助工具,無需誇大其能力。鑑於今年下半年除了 MeMe 之外缺乏顯著的財富效應敘事,圍繞 AI Agent 的炒作圍繞 MeMe 是很正常的。僅依靠 MeMe 無法維持長期價值,因此如果 AI Agent 能夠為交易流程帶來更多創新玩法並提供有形價值,它們可能會發展成為一種通用的基礎設施工具。

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