科普：什么是人工智能？

What Is Artificial Intelligence?

Artificial intelligence, better known as AI, sounds like something out of a science-fiction movie. Now, AI is already a big part of our everyday lives.
人工智能，它更广为人知的名字是AI，这听起来像是科幻电影里的东西。现在，人工智能已经成为我们日常生活的重要组成部分。

If you're curious about AI, you're not alone.
如果你对人工智能感到好奇，你并不是一个人。

It's an important topic because the future of AI will shape everything from the internet to medical technology to our careers —for better and for worse. While AI will open up a whole new world, with real robots helping in ways you probably never imagined.
这是一个重要的话题，因为人工智能的未来将塑造从互联网到医疗技术再到我们的职业生涯的一切——无论是好是坏。而人工智能也将开启一个全新的世界，真正的机器人将以你可能从未想象过的方式（为你）提供帮助。

In a nutshell, artificial intelligence is simply a machine that can mimic a human's learning, reasoning, perception, problem-solving and language usage. An AI computer is programmed to "think," and this process hinges on programming that is called machine learning (ML) and deep learning (DL).
简而言之，人工智能就是一台可以模仿人类学习、推理、感知、解决问题和语言使用的机器。人工智能计算机被编写为可以“思考”（的程序），这个过程取决于被称为机器学习 (ML) 和深度学习 (DL) 的编程。

With ML and DL, a computer is able to take what it has learned and build upon it with little to no human intervention. But there are a few key differences between the two.
有了机器学习和深度学习，计算机可以在几乎没有人为干预的情况下，将所学到的知识运用到实际工作中。但这两者之间也有一些重要的区别。

In machine learning, a computer can adapt to new situations without human intervention, like when Siri remembers your music preference and uses it to suggest new music. Deep learning, on the other hand, is a subset of machine learning inspired by the structure of the human brain. As you may have guessed, this helps it to "think" more like a person.
在机器学习中，计算机可以在没有人为干预的情况下适应新情况，比如Siri会记住你的音乐偏好，并以此为你推荐新的音乐。另一方面，深度学习是机器学习的一个子集，其灵感来源于人类大脑的结构。正如你可能已经猜到的，这有助于它更像一个人一样“思考”。

Essentially, machine learning uses parameters based on descriptions of data, whereas deep learning also uses data that it already knows. AI will also play a big role in the metaverse in the future.
从本质上讲，机器学习使用的是基于数据描述的参数，而深度学习使用的也是它已经知道的数据。未来，人工智能还将在元宇宙中发挥重要作用。

In 1935, Alan Turing envisioned machines with memory that could scan that memory for information. That idea eventually spawned the first digital computers, and in 1950, Turing developed a method to assess whether a computer is intelligent. The Turing Test involves asking a number of questions and then determining if the person responding is a human or a computer. If the computer fools enough people, it is considered thinking or intelligent.
1935年，艾伦 · 图灵设想了一种拥有记忆的机器，这种机器可以通过扫描这些记忆来获取信息。这个想法最终催生了第一台数字计算机。1950年，图灵开发出一种评估计算机是否智能的方法。图灵测试包括提出一些问题，然后判断回答者是人类还是计算机。如果计算机骗过的人足够多的话，它就被认为是会思考的或智能的。

It wasn't until 1955, however, that scientist John McCarthy coined the term "AI".
然而，直到1955年，科学家约翰 · 麦卡锡才创造了“人工智能”这个词。

How does AI work?
人工智能是如何工作的呢?

This essentially boils down to（归结为） how AI learns, and it's a lot like how a parent might teach a child. As AI has matured, it's been trained more through trial and error. The AI makes mistakes, and like a parent, humans provide it with course correction and necessary context. As AI gets better at certain things, some of the rules established early on can be removed creating further opportunities for growth.
这在本质上是由于人工智能的学习方式，就像父母教育孩子一样。随着人工智能逐渐成熟，它更多地是通过试错进行训练。人工智能会犯错，而人类会像父母一样为它提供纠正和必要的背景知识。随着人工智能在某些方面做得越来越好，早期制定的一些规则就可以被取消，从而创造出更多的成长的机会。

Of course, it doesn't have a human brain's neurons. Instead, a computer uses programming given to it by a human, or its algorithms process data to learn.
当然，人工智能没有人脑的神经元。相反，计算机使用人类给它的程序，或者它的算法处理数据来学习。

AI's ability to get smarter over time makes it capable of producing solutions for previously unsolvable or challenging problems.
随着时间的推移，人工智能变得越来越聪明，这使它能够为以前无法解决或具有挑战性的问题提供解决方案。

For example, AI can learn to see connections in data sets that are way too complex for humans. This can lead to innovations like engineering better traffic flow in cities or predicting health problems in large demographics（人口统计） of people, and it can work with virtual reality to create digital models and other immersive experiences.
例如，人工智能可以学会发现数据集之间的联系，这对人类来说非常复杂。这一过程可以带来创新，比如在城市中设计更好的交通线路，或者预测大量人口的健康问题。人工智能还能与虚拟现实技术相结合，可以创建数字模型和其他身临其境的体验。

整理：2024年7月24日于普洱金融培训中心