什麼是Bittensor（Tao）？

Bittensor通過開發由區塊鏈動力並受激勵措施驅動的分散的AI網絡來挑戰集中的AI系統。陶是本地令牌

Bittensor is aiming to build a decentralized AI network with blockchain and token incentives, in contrast to the dominant centralized systems like OpenAI's ChatGPT.

Bittensor的目標是與Openai的Chatgpt（例如Openai的Chatgpt）相比，使用區塊鍊和代幣激勵措施來建立一個分散的AI網絡。

Key Takeaways:

關鍵要點：

Bittensor's goal is to create a decentralized network of AI systems that operate like a global brain or ‘Neural Network’, which allows AI systems to learn from each other and evolve collectively.

Bittensor的目標是建立一個像全球大腦或“神經網絡”一樣運行的AI系統的分散網絡，該網絡使AI系統可以相互學習並集體發展。

The Yuma Consensus evaluates the contributions of network participants by aggregating evaluations assigned by validators to miners. Those who contribute more effectively to the network's intelligence are rewarded accordingly.

YUMA共識通過匯總驗證者分配給礦工的評估來評估網絡參與者的貢獻。那些對網絡智能做出更有效貢獻的人會得到相應的獎勵。

The TAO token is used for registration, staking, and as payment for services within the network, facilitating all economic activities on Bittensor.

TAO令牌用於註冊，積分和作為網絡中的服務付款，從而促進了Bittensor上的所有經濟活動。

The Role of Decentralized AI in the Future of Technology

分散AI在技術未來的作用

Over the last two years, artificial intelligence has progressed at an unprecedented rate but at the same time raised serious concerns around issues like data ownership, algorithmic bias, and centralized control.

在過去的兩年中，人工智能以前所未有的速度發展，但與此同時，人們對數據所有權，算法偏見和集中控制等問題引起了嚴重的關注。

Several projects are innovating at the intersection of AI and blockchain to help build a more open and trustworthy AI ecosystem.

在AI和區塊鏈的交集中，有幾個項目正在創新，以幫助建立一個更開放和值得信賴的AI生態系統。

“The discovery problem is happening with AI right now—you have something that was inherently based on sharing information, sharing research, sharing science. It (was) completely open and (is) now closed into five companies, and these five companies are building tools that we will all become entirely dependent upon; and because they're so complicated, we have no idea how to verify the correctness. We have no idea to verify how they work, what they're actually doing. And because we become so dependent on them, if you let just a few months or a few years go by it becomes too late because those dependencies are so strong so I think it really important that we have an open source alternative to these closed companies.”

“發現問題現在正在與AI一起發生 - 您本質上是基於共享信息，共享研究，共享科學的東西。它完全開放了，現在（現在）將五家公司關閉，這五家公司正在建立我們都完全依賴的工具，我們都會變得非常依賴；並且因為它們是如此復雜，因為他們不知道您如何驗證他們的問題，所以我們可以驗證自己的工作，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式，因為他們的工作方式。幾個月或幾年的時間已經太晚了，因為這些依賴性非常強大，因此我認為我們對這些封閉的公司有一個開源替代方案非常重要。”

Jack Dorsey & Lyn Alden | The Power of Open Source

傑克·多爾西（Jack Dorsey）和林恩·奧爾登（Lyn Alden）|開源的力量

Bittensor Network: The Neural Internet with Subnet Architecture

Bittensor網絡：帶子網結構的神經互聯網

Bittensor operates as a decentralized network of AI models, where miners run AI models across 93 subnets to compete based on specific criteria. Subnets on Bittensor are specialized mini-networks that focus on specific AI tasks, where models compete for rewards (TAO) based on performance, and their performance is assessed and ranked by validators.

Bittensor作為AI模型的分散網絡運行，礦工在93個子網上運行AI模型以根據特定標準競爭。 BITTENSOR上的子網是專門的迷你網絡，專注於特定的AI任務，在該任務中，模型基於性能競爭獎勵（TAO），其性能將由驗證者評估和排名。

The subnets handle tasks such as text generation, image generation, text-to-speech, and model fine-tuning as we will see below.

該子網處理諸如文本生成，圖像生成，文本到語音和模型微調之類的任務，如下所示。

The core idea is that monetary incentives will naturally attract the top-performing models and innovators to the most relevant subnets, which creates a "horse racing for AI models" environment.

核心思想是，貨幣激勵措施自然會吸引最重要的模型和創新者進入最相關的子網，從而創造了“為AI模型的賽馬”環境。

Bittensor is an ideal platform for projects looking to solve computationally expensive AI problems with a high demand. Some advantages of building on Bittensor include:

BITTENSOR是尋求解決需求較高的計算昂貴的AI問題的項目的理想平台。 BITTENSOR建設的一些優勢包括：

The verification system, which ensures the accuracy and quality of the AI-generated data through the miner-validator loop.

驗證系統可確保通過礦工涉足器環路的AI生成數據的準確性和質量。

The ability to deliver cost-effective solutions by replacing human annotators with LLMs.

通過用LLM替換人類註釋者來提供具有成本效益的解決方案的能力。

The potential for monetization of the digital commodity.

數字商品貨幣化的潛力。

Those who contribute more effectively to the network's intelligence are rewarded accordingly.

那些對網絡智能做出更有效貢獻的人會得到相應的獎勵。

Why Bittensor Matters

為什麼Bittensor很重要

Bittensor was founded on the idea that anyone with specialised resources and knowledge could contribute to decentralized AI. At the same time, by creating competition within its ecosystem, Bittensor ensures that only the most efficient, reliable, and innovative subnets are rewarded with more TAO tokens, while subnets with lower performance receive less TAO tokens and may even be removed from the network.

Bittensor建立在這樣的想法中，任何具有專業資源和知識的人都可以為分散的AI做出貢獻。同時，通過在其生態系統中創建競爭，Bittensor確保只有最有效，最可靠和創新的子網才能獲得更多的TAO令牌，而性能較低的子網則獲得較少的TAO令牌，甚至可以將其從網絡中刪除。

One key element of Bittensor is its decentralized nature, which reduces the risk of a single entity controlling the flow of information and censoring content. While centralized platforms are currently acting in ‘good faith’, they remain opaque, and there's always the possibility that this could change in the future.

BITTENSOR的一個關鍵要素是其分散的性質，它降低了控制信息流和審查內容的單個實體的風險。儘管集中式平台目前正在以“誠信”為首，但它們仍然不透明，並且總是有可能在未來發生變化。

A decentralized environment like Bittensor could offer a higher degree of censorship resistance, which is a significant selling point as mainstream AI platforms become increasingly trained to avoid sensitive topics or provide biased responses. We understand that the value of an alternative AI solution that tells the "truth" becomes exponentially higher.

像BITTENSOR這樣的分散環境可以提供更高程度的審查制度抵抗力，這是一個重要的賣點，因為主流AI平台越來越受過訓練，以避免敏感的主題或提供有偏見的響應。我們了解到，講述“真相”的替代AI解決方案的價值變得指定更高。

How Bittensor Works

Bittensor的工作原理

The Bittensor ecosystem consists of a diverse range of participants, all of whom help to ensure that the best AI models rise to the top.

Bittensor生態系統由各種各樣的參與者組成，所有參與者都有助於確保最佳的AI模型上升到最高。

Subnet owners: Individuals or organizations that devise the model for their subnet, its incentive mechanism, and develop the code for both miners and validators.

子網所有者：為其子網設計模型的個人或組織，其激勵機制，並為礦工和驗證者制定代碼。

Miners: Miners that host the AI models available to the subnet, and are responsible for processing queries and generating knowledge. They receive TAO based on their contributions to the network.

礦工：託管子網可用的AI模型的礦工，並負責處理查詢和生成知識。他們根據對網絡的貢獻而收到陶。

Validators: Validators act as evaluators within the network, assessing the quality and effectiveness of AI models when managing user requests.

驗證者：驗證者充當網絡中的評估者，在管理用戶請求時評估AI模型的質量和有效性。

Delegators: Delegators can stake TAO to a validator to receive a share of rewards earned by the validator.

代表人：代表們可以將tao放到驗證者身上，以獲得驗證者獲得的獎勵。

Consumers: Consumers are end-users that query the network, and pay for this information with TAO.

消費者：消費者是查詢網絡的最終用戶，並與Tao付款。

What Are Subnets on Bittensor?

Bittensor上的子網是什麼？

Bittensor is a Layer 1 blockchain with subnets

BITTENSOR是帶子網的1層區塊鏈