ASI-1 mini：fetch.ai啟動了第一個Web3本地大語言模型（LLM），以促進自主代理工作流程

Fetch.ai Inc.是人工無效（ASI）聯盟的創始成員之一，已推出ASI-1 Mini，這是第一個Web3本地大語模型（LLM）

Artificial Superintelligence (ASI) Alliance founding member Fetch.ai Inc., has unveiled ASI-1 Mini, the first Web3-native large language model (LLM) designed to promote autonomous agent workflow, as reported to Finbold on Tuesday, February 25.

人工超級智能（ASI）聯盟創始成員Fetch.ai Inc.已揭幕了ASI-1 Mini，這是第一個旨在促進自主代理工作流程的Web3本地大語言模型（LLM），如2月25日星期二向Finbold報導。

The model, powered by the FET token through ASI wallet integration, marks the beginning of the ASI:

該模型由FET令牌通過ASI錢包的整合提供動力，標誌著ASI的開始：

Picks for you

為您選擇

The AI model is immediately accessible to FET holders, as part of a tiered freemium model.

作為分層免費增值模型的一部分，FET持有人可以立即訪問AI模型。

ASI-1 Mini

ASI-1 mini

Featuring four dynamic reasoning modes — Multi-Step, Complete, Optimized, and Short Reasoning — ASI-1 Mini promises advanced adaptive reasoning and context-aware decision-making.

ASI-1 Mini具有四種動態推理模式 - 多步，完整，優化和簡短的推理 - 承諾先進的自適應推理和上下文感知的決策。

According to Humayun Sheikh, Fetch.ai CEO and ASI Alliance chairman, ASI-1 Mini will lay the foundation for a new decentralized ecosystem:

根據Humayun Sheikh，Fetch.ai首席執行官兼ASI聯盟主席的說法，ASI-1 Mini將為一個新的分散生態系統奠定基礎：

“ASI-1 Mini is the first major product from the ASI Alliance’s innovation stack, marking the beginning of the ASI:

“ ASI-1 Mini是ASI聯盟創新堆棧中的第一個主要產品，標誌著ASI的開始：

rollout and a new era of community-owned AI. … ASI-1 Mini is just the start — over the coming days, we will be rolling out advanced agentic tool-calling, expanded multi-modal capabilities, and deeper Web3 integrations.”

推出和社區擁有的AI的新時代。 …ASI-1 Mini僅僅是開始 - 在接下來的幾天裡，我們將推出高級代理工具稱呼，擴展的多模式功能和更深的Web3集成。”

Instead of relying on a more traditional monolithic approach, ASI-1 Mini dynamically selects specialized AI models optimized for specific tasks.

ASI-1 Mini不依賴更傳統的整體方法，而是動態選擇針對特定任務優化的專業AI模型。

With this system, comprising a foundational intelligence layer (i.e., ASI-1 Mini itself), a specialized model marketplace (MoM Marketplace), and a network of action-driven agents, the model enhances execution capabilities across a wide range of unique applications.

借助該系統，包括基礎智能層（即，ASI-1 Mini本身），專門的模型市場（MOM Marketplace）以及一個以動作驅動的代理網絡的網絡，該模型可以增強廣泛獨特應用程序的執行能力。

High GPU-efficiency

高GPU效率

ASI-1 Mini is designed to deliver enterprise-grade AI performance while operating on just two graphical processing units (GPUs).

ASI-1 MINI旨在在僅使用兩個圖形處理單元（GPU）操作時提供企業級AI性能。

The benchmark results of the approach include greater hardware efficiency (up to x8), lower infrastructure costs, and increased scalability.

該方法的基準結果包括更高的硬件效率（最高X8），較低的基礎設施成本以及可擴展性的提高。

On the Massive Multitask Language Understanding benchmark, ASI-1 Mini was also able to match or outperform leading AI models in domains such as medical sciences, history, and business analytics.

在大規模的多任務語言理解基准上，ASI-1 MINI還能夠匹配或超越醫學科學，歷史和業務分析等領域的領導AI模型。

Soon, the model will be expanded with an extended context window, allowing it to process larger amounts of information (up to ten million tokens as opposed to the initially supported one million).

很快，該模型將通過擴展的上下文窗口擴展，從而使其可以處理大量信息（與最初支持的一百萬個相比，最多一千萬個令牌）。

Addressing the black-box problem

解決黑框問題

In addition to tackling performance issues, ASI-1 Mini will also help address the black-box problem in AI.

除了解決績效問題外，ASI-1 MINI還將有助於解決AI中的黑盒問題。

Unlike traditional models, which generate responses without explaining how they came up with them, ASI-1 relies on multi-step reasoning, allowing for real-time self-correction and improved decision-making transparency.

與傳統模型不同，它在沒有解釋它們如何提出的情況下產生了響應，ASI-1依賴於多步推理，可以實時自我糾正和提高決策透明度。

This is crucial in industries such as healthcare, where precision and clarity are of utmost importance.

這對於醫療保健等行業至關重要，在醫療保健中，精度和清晰度至關重要。

The ASI:

SI：

initiative

倡議

As mentioned, ASI-1 Mini plays a central role in the ASI:

如前所述，ASI-1迷你在ASI中起著核心作用：

initiative set to empower the Web3 community and encourage end-users to participate in AI development directly.

旨在增強Web3社區並鼓勵最終用戶直接參與AI開發的倡議。

Through a decentralized compute network, users can stake, train, and own their own AI models so that the financial rewards of AI advancements can be distributed more fairly.

通過分散的計算網絡，用戶可以利用，培訓和自己的AI模型，以便可以更公平地分發AI進步的財務回報。

ASI-1 Minialso promises real-time execution, autonomous workflows, scalable deployment with minimal computational overhead, and enhanced knowledge representation.

ASI-1 Minialso承諾實時執行，自主工作流，可擴展的部署，並以最少的計算開銷和增強的知識表示。

Users will, therefore, soon be able to deploy AI agents capable of executing real-world tasks ranging from accommodation booking to managing more intricate financial transactions.

因此，用戶將很快能夠部署能夠執行現實世界任務的AI代理，從住宿預訂到管理更複雜的財務交易。