标题： 区块链上的动态大语言模型 显示英文标题

标题： Dynamic Large Language Models on Blockchains

摘要： 训练和部署大型语言模型需要大量的计算资源，因为语言模型包含数十亿个参数，文本包含数千个标记。 另一个问题是大型语言模型是静态的。它们在训练过程之后是固定的。 为了解决这些问题，本文提出在区块链上训练和部署动态大型语言模型，区块链具有高性能计算能力并且分布在计算机网络中。 区块链是一种安全、去中心化且透明的系统，允许创建无需中介的防篡改交易记录。 动态大型语言模型可以在训练过程后持续从用户输入中学习。 我们的方法提供了一种开发大型语言模型的新方式，并为下一代人工智能系统指明了方向。 显示英文摘要

摘要： Training and deploying the large language models requires a large mount of computational resource because the language models contain billions of parameters and the text has thousands of tokens. Another problem is that the large language models are static. They are fixed after the training process. To tackle these issues, in this paper, we propose to train and deploy the dynamic large language model on blockchains, which have high computation performance and are distributed across a network of computers. A blockchain is a secure, decentralized, and transparent system that allows for the creation of a tamper-proof ledger for transactions without the need for intermediaries. The dynamic large language models can continuously learn from the user input after the training process. Our method provides a new way to develop the large language models and also sheds a light on the next generation artificial intelligence systems.