What is Natural Language Processing (NLP)? Please provide a few examples of NLP applications.

Okay, no problem. When it comes to NLP, it's actually not as mysterious as it sounds; it has quietly integrated into our lives.

---

What is Natural Language Processing (NLP)?

You can imagine Natural Language Processing (NLP) as "teaching computers to speak human language."

We humans are naturally capable of speaking, writing, reading, and understanding language, but computers themselves only understand machine code made up of 0s and 1s. What NLP does is build a bridge, allowing computers to understand, interpret, and even generate the languages we use daily (such as Chinese and English).

Its goal is to enable machines to understand what we say and read what we write, just like humans, and to respond in a way we can comprehend.

A Few Examples of NLP Applications

You're definitely familiar with the following examples; NLP is behind all of them:

• Smart Customer Service and Chatbots

  You've surely used Apple's Siri, Xiaomi's Xiao Ai, or interacted with robot customer service on shopping websites, right? When you ask, "What's the weather like today?", it understands and tells you the forecast. When you ask, "Where's my package?", it comprehends and helps you track it. This is NLP at work.

• Machine Translation

  This is very common, like Google Translate or Youdao Dictionary. You input a piece of Chinese text, and it can quickly translate it into English, Japanese, or other languages. Current translation software is becoming increasingly "faithful, expressive, and elegant" (信达雅), translating more and more like human speech, precisely because NLP technology is continuously advancing.

• Sentiment Analysis

  This one is also very interesting. For example, after a movie is released, film companies want to know what the public opinion is like. They can use NLP technology to crawl movie reviews on Weibo and Douban, and then analyze whether these comments are positive reviews (positive sentiment) or negative reviews (negative sentiment). This allows them to quickly grasp public sentiment without having to read through each one individually.

• Spam Filtering

  Why can your email inbox (like QQ Mail or Gmail) automatically throw those annoying advertisements and scam emails into the "junk folder"? It's because it uses NLP technology to analyze the subject and content of each email, identifying keywords (such as "discount," "winning," "invoice") and writing styles to determine if it's spam.

• Text Summarization and Information Extraction

  What do you do when faced with a tens-of-thousands-word report or a lengthy news article that makes your head spin? NLP can help you! Some tools now can automatically read the full text, then extract the most important information, generating a brief summary that allows you to grasp the main idea of the article in just a few minutes.

In summary, NLP is like a "language expert," striving to make machines smarter and more understanding of us. I hope this explanation gives you a more intuitive understanding of it!