That's why grounding the LLM in data is so important.

这就是为什么以数据为基础的 LLM 如此重要。

An llm is of little use to someone picking asparagus.

LLM 对于采摘芦笋的人来说用处不大。

That leaves open the possibility that children have an inborn tendency to grammar, making them far more proficient than any LLM.

这就带来了一种可能性，那就是儿童天生就有语法倾向，这使他们比任何大型语言模型都更擅长语言。

But other researchers have tried to train an LLM on a database of only child-directed language (that is, of transcripts of carers speaking to children).

但其他研究人员试图用只面向儿童的语言数据库(即照顾孩子的人对儿童所说话语的文字稿)来训练大型语言模型。

One of the wildcards is open-source AI, which has proliferated since March, when LLAMA, the LLM developed by Meta, leaked online.

通配符之一是开源 AI，自 3 月以来激增，当时由 Meta 开发的 LLAMA 在线泄露。

(laughs) - So, that takes us back to prompt engineering of noticing how to be a better prompt engineer of an LLM.

（笑）-所以，这让我们回到提示工程，注意如何成为一名更好的法学硕士提示工程师。

Within six months of its launch, Microsoft released ChatGPT-powered Bing; Google demoed its latest large language model (LLM), Bard; and Meta released LLaMA.

推出后六个月内，微软发布了由 ChatGPT 支持的 Bing；谷歌演示了其最新的大型语言模型（LLM）Bard； Meta 发布了 LLaMA。

After all, GPT-3 (the LLM underlying ChatGPT until the recent release of GPT-4) is estimated to be trained on about 1,000 times the data a human ten-year-old is exposed to.

毕竟，GPT-3(在最近发布GPT-4之前，它是ChatGPT的底层语言模型)接受的训练数据大约是一个十岁人类儿童所接触的数据量的1000倍。

" An LLM is designed to produce text that reflects patterns found in its vast training data, " or some such explanation, will help readers take any later imagery with due scepticism.

“大型语言模型用于生成文本，这种文本反映了从其海量训练数据中发现的模式”，或某种类似的解释，这种说法将帮助读者对之后出现的任何意象持以适当的怀疑态度。

In a forthcoming paper in Linguistic Inquiry, researchers claim to have trained an LLM on no more text than a human child is exposed to, finding that it can use even rare bits of grammar.

在即将发表在《语言研究》杂志上的一篇论文中，研究人员声称，用不超过人类儿童所接触的文本量的数据训练一个大型语言模型，发现它甚至可以使用很少见的语法。