It's an obvious fact that computers and the Internet have permeated every aspect of our lives and will do so for the foreseeable future. They are everywhere, from socializing, to eating, drinking, and learning, to the fact that you can open this article on your phone and start reading, and none of it is possible without the development of computer and programming technology. Computer technology clearly has a crucial role to play in the future development of a country.

But you may be wondering: what does programming have to do with me when I'm just a liberal arts student/I'm not in IT?

Tell me about my own understanding. Everyone must have used Google Translate, right? Do you remember what Google Translate was like 5 years ago, 10 years ago? Is there any feeling that the quality of Google Translate is getting better and better? (Though there is still a big gap with human translation) and how did this happen?

The important key to Google Translate's improved quality is not breakthroughs in linguistics and corpus research, but because of one technology: big data.

Before the advent of big data, traditional machine translation probably followed the following rules: set up the best possible set of grammatical rules and a lexicon of words for both languages, and then translate the input according to that set of rules. In order to improve the grammatical rules and thesaurus, machine translation research organizations once employed many linguistics and translation experts, but the final result was not satisfactory after a long time of research. For example, because machine translators were so fixated on grammatical rules, translating the phrase "It serves him right." could yield absurd results like "It serves him right.

It wasn't until the advent of big data technology that machine translation broke new ground. Simply put, translation using big data is not done according to grammatical rules, but according to correlations between data and machine learning algorithms. For example, when translating the sentence "It serves him right." Google does not translate the sentence word by word, but puts the whole sentence into the Internet database to search, and then counts all the results on the Internet related to the translation of this sentence (for example, various Chinese-English articles may appear in the sentence and the translation of the control), and the translation with the highest number of counts can be used as the final answer. Reference. Through such processing, Google can ensure that the translated results are the most popular on the Internet, the most accepted by users, and the quality of the translation has been greatly improved.

This is a successful application of computer technology in the field of translation.

This example is given to show that even the purely liberal arts field of translation will inevitably intersect with computer technology, not to mention other disciplines. In fact, in Europe and the United States university liberal arts students to learn programming is nothing new, many liberal arts students have already begun to use Python (a scripting language) for text mining as well as data processing. There are also universities in China that offer cross-curricular courses in computer science and linguistics, such as a course called "Computational Linguistics," which is basically the study of the English language using programming and math, so if you're interested, you can learn more about it.

So programming is a very important skill now and in the future, both for profit and as a hobby.

Knowing how to program can bring you a lot of practical benefits. For example, if you know how to program, you can write a crawler to grab the words you're interested in from the major dictionary sites, create a vocabulary book, count high-frequency words, and capture first-hand listening and reading material from the foreign media. There are many more interesting applications, depending on your imagination and creativity.