环境利用Solana的高速和效率，引入了逻辑证明（POL）机制

随着区块链和人工智能技术的发展，如何有效地结合两者已成为目标之一

As blockchain and artificial intelligence technologies continue to develop, how to effectively combine the two has become one of the goals of many innovative projects. Ambient was born in this context, dedicated to combining decentralized blockchain architecture with ultra-large-scale AI reasoning to explore a new intelligent economic model.

随着区块链和人工智能技术的不断发展，如何有效地结合两者已成为许多创新项目的目标之一。环境是在这种情况下诞生的，致力于将分散的区块链体系结构与超大规模的AI推理相结合，以探索一种新的智能经济模型。

As a complete fork of Solana, Ambient retains Solana's high speed and efficiency, and creates a brand new blockchain ecosystem by introducing the Proof of Logits (PoL) mechanism.

作为一个完整的Solana叉，环境保留了Solana的高速和效率，并通过引入逻辑（POL）机制来创建一个全新的区块链生态系统。

What is Ambient?

什么是环境？

Ambient is a Layer-1 blockchain that combines Solana SVM compatibility with a novel proof-of-work mechanism to provide ultra-large-scale verified reasoning. The core concept of the Ambient project is to deeply integrate AI reasoning and blockchain to create a decentralized AI economy.

环境是一个1层区块链，将Solana SVM兼容性与新颖的工作证明机制相结合，以提供超大规模的验证推理。环境项目的核心概念是深入整合AI推理和区块链，以创建分散的AI经济。

Unlike traditional proof-of-stake (PoS) systems, Ambient uses an incentive mechanism similar to Bitcoin and provides predictable profits for each node that participates in network reasoning, fine-tuning, or training. This approach avoids reliance on enterprise-level GPUs and ensures sustainable profitability for miners through transaction- and inflation-based compensation. Both miners and users can receive rewards that match their contributions, and the value of the platform continues to increase as the network grows.

与传统的证明（POS）系统不同，环境使用类似于比特币的激励机制，并为参与网络推理，微调或培训的每个节点提供可预测的利润。这种方法避免依赖企业级的GPU，并通过基于交易和通货膨胀的薪酬确保矿工的可持续盈利能力。矿工和用户都可以收到与其贡献相匹配的奖励，并且该平台的价值随着网络的增长而继续增加。

Features of Ambient:

环境的特征：

Ambient team background and development status

环境团队的背景和发展状况

In addition to the background of the founder, Ambient has not yet disclosed information about other members. Ambient's CEO and founder Travis Good has a diverse academic background, and his academic career covers four fields: government, economics, computer science, and machine learning. Travis' leadership style focuses on execution and pragmatism. When promoting technological innovation, he always adheres to practical operations and focuses on executable solutions. In addition, Travis is very active on Twitter and often shares his unique insights on technology, innovation, and industry trends.

除了创始人的背景外，Ambient尚未披露有关其他成员的信息。 Ambient的首席执行官兼创始人Travis Good具有多样化的学术背景，他的学术生涯涵盖了四个领域：政府，经济学，计算机科学和机器学习。特拉维斯的领导风格着重于执行和实用主义。在促进技术创新时，他始终遵守实践运营，并专注于可执行的解决方案。此外，特拉维斯（Travis）在Twitter上非常活跃，并且经常分享他对技术，创新和行业趋势的独特见解。

On April 1, Ambient completed a $7.2 million seed round of financing, led by a16z CSX, Delphi Digital, and Amber Group. Big Brain Holdings, Superscrypt, Proof Group, Rubik Ventures, Aethir Foundation, Edessa Capital, etc. participated in the investment. Ambient plans to launch a testnet in the second/third quarter.

4月1日，Ambient完成了由A16Z CSX，Delphi Digital和Amber Group领导的720万美元种子融资。大脑持有，SupersCrypt，Proof Group，Rubik Ventures，Aethir Foundates，Edessa Capital等。环境计划在第二/第三季度启动测试网。

Logits Proof of Consensus Mechanism

共识机制的逻辑证明

The "Logits Proof" algorithm takes advantage of a key fact: logits (which can be understood as logical units) are both unique fingerprints and can effectively capture the "thinking" state of the model at a specific moment (that is, when the model is "streaming" output) through the hash value generated during the model generation process. Under this mechanism, the hash value of the logits proof is a hash list of each set of logits hash values before each output token. In short, for each token n, until the final token t, the hash value of the logits proof is:

“ logits证明”算法利用了一个关键事实：logits（可以理解为逻辑单元）既是独特的指纹，又可以在特定时刻（即，当模型是“流”输出“流”输出）通过模型生成过程中的哈希值有效地捕获模型的“思维”状态。在此机制下，逻辑证明的哈希值是每个输出令牌之前的每组逻辑哈希值的哈希列表。简而言之，对于每个令牌n，直到最终令牌t为止，logits证明的哈希值是：

Hash(Hash(n) … Hash(t))

哈希（哈希（n）…哈希（t））

The hash value of the logits progress token proof is the logits hash after generating x tokens, where x is between n and t (inclusive), that is:

logits进度标记的哈希值是生成x令牌后的logitts哈希，其中x在n和t之间（包含在内），也就是说：

Hash(n) … Hash(x) … Hash(t)

哈希（n）…哈希（x）…哈希（t）

Based on this principle, a verification mechanism can be constructed: first, the miner generates text; then, the verifier randomly selects a word in the text and asks the miner to provide the "mental state" at that point (that is, the corresponding logits progress mark proof hash). Then, the verifier performs a reasoning on the word in the same model and context to generate its own "mental state". If the "mental states" of the two (represented by hash values) are consistent, the verification is successful.

基于此原则，可以构建验证机制：首先，矿工生成文本；然后，验证者随机选择文本中的单词，并要求矿工在此时提供“精神状态”（即，相应的logitts进度标记标记标记哈希）。然后，验证者在同一模型和上下文中对单词进行推理，以生成自己的“精神状态”。如果两者的“精神状态”（由哈希值表示）是一致的，则验证是成功的。

This proof-of-work mechanism is consistent with the design principles of Bitcoin: mining (in this case, repeatedly executing the model through inference of 4,000 tokens) is expensive, but the verification process is very cheap (only 1 token is required for inference). This mechanism not only improves efficiency, but also ensures the security and reliability of verification.

这种工作证明机制与比特币的设计原理一致：采矿（在这种情况下，通过推断4,000个令牌反复执行模型）很昂贵，但是验证过程非常便宜（推理只需要1个令牌）。这种机制不仅提高了效率，而且还确保了验证的安全性和可靠性。