Swarms：科技人群的另一個入口？

隨著比特幣下跌、山寨幣翻紅，一線鏈上的梗暫時成為市場的「避風港」。

Bitcoin's decline and the overall red altcoin market have caused first-tier chain memes to temporarily become the "safe haven" of the market. Although some high-market-cap memes listed on exchanges are inevitably affected by the overall market and continue to decline, for new popular assets (or more appropriately called "fast-track assets"), the panic in the market can at most cause some superficial injuries.

比特幣的下跌以及山寨幣市場整體的紅色，讓一線鏈迷暫時成為了市場的「避風港」。雖然一些在交易所上市的高市值表情包不可避免地會受到整體市場的影響而持續下跌，但對於新的熱門資產（或更恰當地稱為“快車道資產”）來說，市場的恐慌最多只能造成一些表淺損傷。

Last Friday, the enterprise-level multi-agent collaboration framework Swarms announced on Twitter that it was "claiming" the token $swarms issued through Pump.Fun. It is termed "claiming" because $swarms did not launch on the day of the official announcement but had already existed two days earlier. Without official endorsement, $swarms might have been regarded by the market as an ordinary "scam," with its market cap once languishing at a low of $6,000.

上週五，企業級多智能體協作框架 Swarms 在 Twitter 上宣布，它正在「認領」透過 Pump.Fun 發行的代幣 $swarms。之所以稱為“聲明”，是因為 $swarms 並未在官方宣布當天啟動，而是在兩天前就已經存在。如果沒有官方背書，$swarms可能會被市場視為一個普通的“騙局”，其市值一度徘徊在6000美元的低點。

With the success of $arc as a precedent, the narrative framework of $swarms led the market to buy in without hesitation. On the "Black Friday" when altcoins plummeted, $swarms merely consolidated sideways during the most panicked hours of the market, before directly breaking through a market cap of $70 million.

以$arc的成功為先例，$swarms的敘事框架引領市場毫不猶豫地買入。在山寨幣暴跌的“黑色星期五”，美元蜂擁而至，只是在市場最恐慌的時段橫盤整理，然後直接突破了 7000 萬美元的市值。

By synthesizing information provided by Swarms' official website and technical documentation, we have a preliminary understanding of what the Swarms framework does.

透過綜合Swarms官網提供的資訊和技術文檔，我們對Swarms框架的作用有了初步的了解。

Note: Meme token prices are highly volatile and carry significant risks. Investors should fully assess risks and participate cautiously. This article only shares information based on market trends, and the author and platform make no guarantees regarding the completeness or accuracy of the content. This article does not constitute any investment advice.

注意：Meme 代幣價格波動很大，有重大風險。投資者應充分評估風險，謹慎參與。本文僅分享基於市場趨勢的訊息，作者和平台不保證內容的完整性或準確性。本文不構成任何投資建議。

Is it another entry for the tech crowd?

這是科技人群的另一個入口嗎？

In addition to the clear token address on the Swarms official homepage, the developer of the Swarms framework @KyeGomezB continued to discuss token-related news on that day.

除了Swarms官方主頁上有明確的代幣地址外，Swarms框架的開發者@KyeGomezB當天也繼續討論代幣相關的新聞。

According to Kye Gomes' GitHub page, the Swarms framework has already received over 2,000 stars (the $arc rig framework currently has 1,300 stars).

根據 Kye Gomes 的 GitHub 頁面，Swarms 框架已經獲得了 2,000 多顆星（$arc rig 框架目前有 1,300 顆星）。

With GitHub as proof, at least the hardcore technical identity of the $swarms token is solidified.

有 GitHub 為證，至少 $swarms 代幣的核心技術身分得到了鞏固。

Enterprise-level Multi-Agent Collaboration Framework

企業級多Agent協作框架

The Swarms framework was not originally designed specifically for Crypto Native services in Web3; its core positioning, as the term "Swarms" suggests, is a multi-agent collaboration framework for enterprises. It is more than just a simple AI development tool; it is a complete solution focused on addressing the practical problems enterprises face during the implementation of AI.

Swarms 框架最初並不是專門為 Web3 中的 Crypto Native 服務設計的；正如“Swarms”一詞所暗示的那樣，其核心定位是企業的多智能體協作框架。它不僅僅是一個簡單的AI開發工具；它是專注於解決企業在實施人工智慧過程中遇到的實際問題的完整解決方案。

In practical applications, Swarms provides a complete toolchain that enables enterprises to easily build and manage collaboration among multiple AI agents. These AI agents can be different language models, specialized tools, or custom intelligent agents, which can seamlessly cooperate under the scheduling of Swarms to complete complex business tasks.

在實際應用中，Swarms提供了完整的工具鏈，使企業能夠輕鬆建立和管理多個AI代理之間的協作。這些AI代理可以是不同的語言模型、專門的工具，也可以是客製化的智慧代理，它們可以在Swarms的調度下無縫協作，完成複雜的業務任務。

From a technical architecture perspective, the Swarms framework includes the following core components:

從技術架構來看，Swarms框架包含以下核心元件：

Task scheduling system: responsible for breaking down complex tasks and assigning them to suitable AI agents.

任務調度系統：負責分解複雜的任務並將其分配給合適的AI代理。

Agent management module: manages the lifecycle and status of each AI agent.

Agent管理模組：管理各個AI Agent的生命週期和狀態。

Communication middleware: ensures accurate and efficient information transfer between agents.

通訊中間件：確保Agent之間準確、有效率的訊息傳遞。

Monitoring and logging system: tracks the operational status of the entire system in real-time.

監控記錄系統：即時追蹤整個系統的運作狀態。

At the enterprise application level, Swarms provides:

在企業應用層面，Swarms 提供：

High availability assurance: automatic fault tolerance and recovery mechanisms.

高可用性保證：自動容錯和復原機制。

Complete monitoring system: real-time tracking of AI agent performance and status.

完整的監控系統：即時追蹤AI代理的效能和狀態。

Flexible scalability: easy addition of new AI capabilities and business logic.

靈活的可擴展性：輕鬆添加新的人工智慧功能和業務邏輯。

Security considerations: comprehensive permission management and data protection mechanisms.

安全性考量：完善的權限管理和資料保護機制。

To understand how Swarms works, we can use an orchestra as an analogy:

為了理解 Swarms 的工作原理，我們可以用管弦樂團來比喻：

Imagine a large orchestra performing a symphony. Traditional AI solutions are like a jack-of-all-trades trying to play all instruments at once. In contrast, Swarms allows each "musician" (AI agent) to focus on their expertise, collaborating under the direction of a "conductor" (Swarms framework). The sheet music represents the standardized task flow of the entire system, while rehearsals are the continuous optimization process of the system.

想像一下大型管弦樂團正在演奏交響樂。傳統的人工智慧解決方案就像一個多才多藝的人，試圖同時演奏所有樂器。相較之下，Swarms 允許每個「音樂家」（AI 代理）專注於他們的專業知識，在「指揮」（Swarms 框架）的指導下進行協作。樂譜代表了整個系統標準化的任務流程，而排練則是系統不斷優化的過程。

For example, in an e-commerce scenario, when a user needs personalized shopping recommendations, the system automatically coordinates multiple specialized agents. The user profiling agent deeply understands user needs, the product recommendation agent filters the most suitable products accordingly, and the review analysis agent organizes user feedback, ultimately presenting friendly suggestions to the user through the dialogue assistant agent. These agents perform their respective roles while seamlessly cooperating to provide precise services to the user.

例如，在電子商務場景中，當使用者需要個人化購物推薦時，系統會自動協調多個專門的代理商。用戶畫像代理深入了解用戶需求，產品推薦代理相應過濾最合適的產品，評論分析代理整理用戶反饋，最終透過對話助理代理向用戶呈現友好的建議。這些代理商各司其職，無縫協作，為用戶提供精準服務。

How does it differ from other projects in the same field?

它與同一領域的其他項目有何不同？

As a product in the AI framework space, whether it is $ai16z&$ELIZA with the ELIZA framework or $arc based on the rig framework, their prices reflect the market's recognition of the underlying infrastructure concept.

作為AI框架領域的產品，無論是採用ELIZA框架的$ai16z&$ELIZA，還是基於Rig框架的$arc，它們的價格都體現了市場對底層基礎設施理念的認可。

So, is the Swarms framework in competition with the other two projects? Or can they complement each other?

那麼，Swarms 框架是否與其他兩個項目存在競爭？或者說它們可以互補嗎？

Twitter user @tmel0211 summarized

Twitter 用戶@tmel0211 總結