[这里提到的本质不仅适用于 ChatGPT,也同样适用于当前的其他“大语言模型”(large language model,LLM)。] 首先需要解释,ChatGPT 从根本上始终要做的是,针对它得到的任何文本产生“合理的延续”。这里所说的“合理”是指,“人们在看到诸如数十亿个网页上的内容后,可能期待别人会这样写”。 (查看原文)...
首先要解释的是,ChatGPT 从根本上说总是试图对它目前得到的任何文本进行 “合理的延续”,这里的 “合理” 是指 “在看到人们在数十亿个网页上所写的东西之后,人们可能会期望某人写出什么”。因此,假设我们已经得到了 “人工智能最好的是它能去做 ……” 的文本(”The best thing about AI is its ability to...
ChatGPT, developed by OpenAI and based on the GPT-4 architecture, is an advanced language model designed to understand and generate text that closely mimics human language. This enables users to engage in seamless conversations, create content, and perform various natural language processing tasks. ...
解析 B 【详解】 句意:——托尼,什么是ChatGPT?——ChatGPT是一个人工智能机器人。它可以像人类一样思考,几乎可以做任何事情。 考查冠词。“AI robot”是可数名词单数,介绍ChatGPT是一种人工智能机器人,表泛指,且“AI”以元音音素开头,前面用不定冠词an。故选B。
And in the case of ChatGPT, lots of such “knobs” are used—actually, 175 billion of them. But the remarkable thing is that the underlying structure of ChatGPT—with “just” that many parameters—is sufficient to make a model that computes next-word probabilities “well enough” to give...
It is worth understanding that there’s never a “model-less model”. Any model you use has some particular underlying structure—then a certain set of “knobs you can turn” (i.e. parameters you can set) to fit your data. And in the case of ChatGPT, lots of such “knobs” are us...
ChatGPT is an AI-based language model developed by OpenAI. ChatGPT has been trained on a large corpus of text data to generate human-like responses to
Being a programmer in ai SPAM LINK REMOVED space, was fortunate to understand the pulse in the technology sector. I believe ChatGPT is going to change the way humans interact with the machines. From a different post that I just posted to but still appropriate... ...
What is Chat GPT? Chat GPT is a communication program, a so-called chatbot, which is based on an artificial intelligence language model. The function ofChat GPTis to react to user requests in a human-like manner and thus – at least virtually – to enable an interaction that seems real....
It’s hard to get a handle on what this layer is doing. But here’s a plot of the 768×768 matrix of weights it’s using (here for GPT-2): 经过注意力头的处理后,得到的“重新加权嵌入向量”(对于GPT-2为长度为768,而对于ChatGPT的GPT-3为长度为12,288)通过一个标准的“全连接”神经网络...