管道本身。 Bittensor 有很大的想像空間，但也面臨許多挑戰。

Bittensor 是一種去中心化的人工智慧基礎設施，人工智慧開發人員使用它來建構和部署機器學習模型或其他人工智慧相關的開發。

the productivity improvement brought by AI technology and the improvement of people's lives.output:Preface

人工智慧技術帶來的生產力提升和人們生活的改善輸出：前言

With the progress of data, computing power, and algorithm research in recent years, AI development has made great breakthroughs, especially the emergence of OpenAI GPT-4. The arrival of the basic LLM large model represented by it has promoted the improvement of productivity and the transformation of social efficiency.

近年來，隨著數據、運算能力、演算法研究的進步，AI發展取得了巨大突破，尤其是OpenAI GPT-4的出現。以它為代表的基礎LLM大模式的到來，推動了生產力的提升和社會效率的轉變。

However, the disadvantages of these closed-source large models represented by GPT-4 have also been revealed, namely, centralized models usually have restrictions on third-party integrations, which undermines the scalability and interoperability of AI agents based on centralized models.

然而，以GPT-4為代表的這些閉源大型模型的缺點也暴露出來，即中心化模型通常對第三方集成有限制，這損害了基於中心化模型的AI代理的可擴展性和互操作性。

Therefore, large open source models such as the Llama series have been sought after by more and more researchers, but open source does not mean transparency, and it also faces many challenges.

因此，像Llama系列這樣的大型開源模型受到了越來越多研究者的追捧，但開源並不意味著透明，也面臨著許多挑戰。

The main difficulty is that for most contributors, open source AI development does not have any economic incentives. Even if there are some competition rewards, these are usually one-off. Subsequent improvement and development work still needs to be done out of love. Unless it reaches a certain scale and has a large community of followers, there will be more possibilities for income and more contributors to continue to improve.

主要困難在於，對於大多數貢獻者來說，開源人工智慧開發沒有任何經濟誘因。即使有一些比賽獎勵，這些通常也是一次性的。後續的改進和開發工作還是需要出於愛心來完成。除非達到某個規模，擁有龐大的追隨者社區，才會有更多的收入和更多的貢獻者繼續提升的可能性。

Therefore, the Bittensor AI project attempts to use web3 token mining to make open source AI development more sustainable, verifiable and efficient. Through Yuma Consensus, we introduce and align resources and research miners, validators, and AI project subnet creators, making the entire AI research more transparent and decentralized. Anyone can participate in AI contributions and win the rewards they deserve.

因此，Bittensor AI計畫嘗試利用web3代幣挖礦，讓開源AI開發更永續、可驗證、更有效率。透過Yuma共識，我們引入並整合資源以及研究礦工、驗證者和AI專案子網創建者，使整個AI研究更加透明和去中心化。任何人都可以參與人工智慧貢獻並贏得應有的獎勵。

The performance of tokens in the secondary market also confirms people’s expectations. The price has increased from more than 50 US dollars in September 2023 to more than 500 yuan in December 2024, a 10-fold increase!

代幣在二級市場的表現也印證了人們的預期。價格從2023年9月的50多美元漲到2024年12月的500多元，漲幅達10倍！

Recently, Bittensor’s investor and founder of Digital Currency Group established Yuma, an accelerator dedicated to incubating subnet projects within the Bittensor ecosystem, and served as its CEO, demonstrating his confidence in and potential for the Bittensor project.

近日，Bittensor的投資人、數位貨幣集團創辦人成立了致力於孵化Bittensor生態內子網計畫的加速器Yuma，並擔任其CEO，展現了他對Bittensor計畫的信心和潛力。

Of course, the success of any project cannot be without doubts. Bittensor has also had a lot of FUD since its inception. In this article, we summarize many questions that have not been fully answered, and try to understand Bittensor's future positioning and possibilities in the decentralized AI track through research and analysis.

當然，任何專案的成功都不可能毫無疑問。 Bittensor 自成立以來也有很多 FUD。在這篇文章中，我們總結了許多尚未完全解答的問題，並試圖透過研究和分析來了解Bittensor在去中心化AI賽道上未來的定位和可能性。

What is Bittensor?

什麼是比特張量？

Founded in 2021 by a team from Toronto, Canada, including Jacob Robert Steeves, Ala Shaabana, and Garrett Oetken, Bittensor is a decentralized AI infrastructure used by AI developers to build and deploy machine learning models or other AI-related developments. Many Web3 AI projects, whether or not they already have their own blockchain, can access Bittensor's blockchain "subtensor" and become one of its subnets.

Bittensor 由來自加拿大多倫多的團隊於2021 年創立，成員包括Jacob Robert Steeves、Ala Shaabana 和Garrett Oetken，是一個去中心化的AI 基礎設施，供AI 開發人員用來構建和部署機器學習模型或其他AI 相關開發。許多Web3 AI項目，無論是否已經擁有自己的區塊鏈，都可以存取Bittensor的區塊鏈「子張量」並成為其子網路之一。

What is a Subnet?

什麼是子網路？

Subnets form the core of the Bittensor ecosystem. Each Bittensor subnet is an independent incentive-based competitive market. Anyone can create a subnet, customize the tasks to be performed by the subnet, and design an incentive mechanism (in the machine learning analogy, the incentive mechanism can be understood as a target loss function that can guide model training towards the desired results). You only need to pay a registration fee (in TAO) to create a subnet, and you can get a netuid for the subnet. Note that a subnet creator does not need to assume the operating tasks within the subnet, but transfers the right to operate the subnet tasks to others.

子網路構成了 Bittensor 生態系統的核心。每個Bittensor子網路都是一個獨立的基於激勵的競爭市場。任何人都可以創建一個子網，定制子網要執行的任務，並設計激勵機制（在機器學習類比中，激勵機制可以理解為目標損失函數，可以指導模型訓練達到期望的結果）。您只需要支付註冊費（以TAO形式）即可建立子網，並且可以獲得該子網路的netuid。需要說明的是，子網路創建者並不需要承擔子網路內的操作任務，而是將子網路任務的操作權轉移給他人。

The task of operating the subnet provides another way for others to participate, that is, to join an existing subnet. If you join an existing subnet, there are two ways to participate: as a subnet miner or a subnet validator. In addition to paying the registration fee denominated in TAO (if you are a validator, you also need to stake TAO), he only needs to provide a computer with sufficient computing resources, and register the computer and his wallet to a subnet, and run the subnet miner module or subnet validator module provided by the subnet builder on this computer (both modules are Python code in the Bittensor API).

操作子網路的任務為其他人提供了另一種參與方式，即加入現有子網路。如果您加入現有子網，有兩種參與方式：作為子網路礦工或子網路驗證者。除了支付以TAO計價的註冊費（如果你是驗證者，還需要質押TAO），他只需要提供一台具有足夠計算資源的計算機，並將計算機和他的錢包註冊到一個子網，並運行該電腦上的子網路建構器提供的子網路挖掘器模組或子網路驗證器模組（這兩個模組都是Bittensor API 中的Python 程式碼）。

How does the competitive market for subnets work?

子網路競爭市場如何運作？

Here’s how the subnet competition works: Let’s say you decide to become a subnet miner. The subnet validator will assign you some tasks to complete. Other miners in the subnet will also receive tasks of the same type. After all subnet miners complete their tasks, they submit the results to the subnet validator.

子網路競爭的運作方式如下：假設您決定成為子網路礦工。子網路驗證器將為您指派一些任務來完成。子網路中的其他礦工也會收到相同類型的任務。所有子網路礦工完成任務後，將結果提交給子網路驗證器。

Subnet validators will then evaluate and rank the quality of the tasks submitted by the subnet miners. As a subnet miner, you will be rewarded (in TAO) based on the quality of your work. Similarly, other subnet miners will also receive corresponding rewards based on their performance. At the same time, subnet validators will also be rewarded for ensuring that high-quality subnet miners receive better rewards, thereby

然後，子網路驗證器將對子網路礦工提交的任務的品質進行評估和排名。作為子網路礦工，您將根據您的工作品質獲得獎勵（以 TAO 形式）。同樣，其他子網路礦工也會根據表現獲得相應的獎勵。同時，子網驗證者也將因確保優質子網礦工獲得更好的獎勵而獲得獎勵，從而