BasedAI is a distributed network of machines which introduces decentralized infrastructure capable of integrating Fully Homomorphic Encryption (FHE) with any large language model (LLM) connected to its network. The proposed framework embeds a default mechanism, called "Cerberus Squeezing", into the mining process which enables the transformation of a standard LLMs into encrypted zero-knowledge LLMs, or "ZK-LLMs", leveraging insights from generative adversarial networks for data privacy. This novel quantization mechanism empowers BasedAI miners to process and respond to prompts derived from User interaction with LLMs without the need for decrypting ei- ther the queries or their corresponding responses. The introduction of Cerberus Squeezing significantly improves performance degradation caused by quantized functions in current FHE-compliant computing environments by proactively optimizing calls between users, miners, and validators.

翻译：BasedAI是一个由机器组成的分布式网络，它引入了能够将全同态加密（FHE）与任何连接至其网络的大型语言模型（LLM）集成的去中心化基础设施。所提出的框架在挖矿过程中嵌入了一种名为"Cerberus Squeezing"的默认机制，该机制能够利用生成对抗网络在数据隐私方面的洞见，将标准LLM转化为加密的零知识LLM（即"ZK-LLMs"）。这种新颖的量化机制使BasedAI矿工能够处理并响应来自用户与LLM交互所产生的提示，而无需对查询或其相应回复进行解密。Cerberus Squeezing的引入通过主动优化用户、矿工与验证者之间的调用，显著改善了当前符合FHE的计算环境中因量化函数导致的性能退化问题。