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      考研英语水平的进步，不仅要记单词，还需要阅读外语文献等资料。接下来，小编为2024考研者们，整理出——2024考研英语同源外刊7月:人工智能，供考生参考。

2024考研英语同源外刊7月:人工智能

When it comes to “large language models” (LLMS) such as GPT—which powers ChatGPT, a popular chatbot made by OpenAI, an American research lab—the clue is in the name. Modern AI systems are powered by vast artificial neural networks, bits of software modelled, very loosely, on biological brains. GPT-3. an LLM released in 2020. was a behemoth. It had 175bn “parameters”, as the simulated connections between those neurons are called. It was trained by having thousands of GPUs (specialised chips that excel at AI work) crunch through hundreds of billions of words of text over the course of several weeks. All that is thought to have cost at least $4.6m.

说到“大型语言模型”(LLMS)，比如GPT——它为ChatGPT提供动力，ChatGPT是美国研究实验室OpenAI制造的一款流行的聊天机器人——名字里就有线索。现代人工智能系统由庞大的人工神经网络驱动，这是一种非常不精确地模仿生物大脑的软件。2020年发布的大型语言模型GPT-3是一个庞然大物。它有1750亿个“参数”，这些神经元之间的模拟连接被称为“参数”。它是通过数千个GPU(擅长人工智能工作的专用芯片)在几周内处理数千亿字的文本来训练的。所有这些被认为至少花费了460万美元。

But the most consistent result from modern AI research is that, while big is good, bigger is better. Models have therefore been growing at a blistering pace. GPT-4. released in March, is thought to have around 1trn parameters—nearly six times as many as its predecessor. Sam Altman, the firm’s boss, put its development costs at more than $100m. Similar trends exist across the industry. Epoch AI, a research firm, estimated in 2022 that the computing power necessary to train a cutting-edge model was doubling every six to ten months.

但现代人工智能研究较一致的结果是，虽然大是好，但越大越好。因此，模特一直在以惊人的速度增长。3月份发布的GPT-4被认为有大约1万亿参数，几乎是其前身的6倍。公司老板萨姆·阿尔特曼(Sam Altman)认为其开发成本超过1亿美元。整个行业都存在类似的趋势。研究公司Epoch AI在2022年估计，训练一个尖端模型所需的计算能力每六到十个月就会翻一番。

This gigantism is becoming a problem. If Epoch AI’s ten-monthly doubling figure is right, then training costs could exceed a billion dollars by 2026—assuming, that is, models do not run out of data first. An analysis published in October 2022 forecast that the stock of high-quality text for training may well be exhausted around the same time. And even once the training is complete, actually using the resulting model can be expensive as well. The bigger the model, the more it costs to run.

这种巨人症正在成为一个问题。如果Epoch AI的10个月翻一番的数据是正确的，那么到2026年，训练成本可能会超过10亿美元——假设模型没有首先耗尽数据。2022年10月发表的一项分析预测，用于培训的文本库存可能会在同一时间耗尽。即使训练完成了，实际使用得到的模型也可能是昂贵的。模型越大，运行成本就越大。

 

单词：

approach /əˈproʊtʃ/ n. 方法;

run out of road 走投无路;快到尽头了;

when it comes to 当谈到…;当提到…;

chatbot/ˈtʃætˌbɒt/ n. 一种聊天程序;聊天机器人;

clue /kluː/ n. 线索;

vast /væst/ adj. 巨大的;

neural/ˈnʊrəl/ adj. 神经的，神经系统的;

loosely /ˈluːsli/ adv. 宽松地;不精确地;

behemoth /bɪˈhiːməθ/ n. 巨兽;

parameter /pəˈræmɪtər/ n. 参数;

simulated /ˈsɪmjuleɪtɪd/ adj. 模拟的;

      综上是“2024考研英语同源外刊7月:人工智能”，希望对备战2024考研考生们有所帮助!让我们乘风破浪，终抵彼岸，考研加油!

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