{"id":8864,"date":"2025-04-14T14:35:07","date_gmt":"2025-04-14T13:35:07","guid":{"rendered":"https:\/\/demo.sidekick.be\/untranslate\/?p=8864"},"modified":"2026-01-20T11:09:53","modified_gmt":"2026-01-20T11:09:53","slug":"what-are-we-talking-about-when-we-talk-about-ai","status":"publish","type":"post","link":"https:\/\/demo.sidekick.be\/untranslate\/what-are-we-talking-about-when-we-talk-about-ai\/","title":{"rendered":"What are we talking about when we talk about AI?"},"content":{"rendered":"
Artificial intelligence … It has become a hot topic<\/em> in recent years, glowing hot even. Everyone is talking about artificial intelligence (AI). In the media, at school or at work, it cannot be missed. But are we always talking about the same thing when we talk about AI? And above all, will AI soon take over our jobs, or are we expecting too much? Following a report in Terzake\u00b9, the Untranslate team asked itself these questions. In this article, we look for the answer and give our take on AI in the language industry.<\/strong><\/h5>\n<\/div><\/div>
<\/div>

AI, a recent discipline … or not?<\/strong><\/h2>\n

AI is gaining considerable momentum. In recent years, it has become indispensable in the daily lives of students, professionals and researchers. Yet it is not a new discipline. The term ‘artificial intelligence’ was first introduced by John McCarthy at a 1956 conference attended by researchers from various fields. That conference and previous successful experiments with different forms of artificial intelligence, such as the Georgetown-IBM experiment, sparked interest and investment in AI research.<\/p>\n<\/div><\/div>

<\/i><\/div>

The Georgetown-IBM experiment was one of the first and most influential demonstrations of machine translation. It took place on 7 January 1954. More than 60 sentences were translated from Russian to English.<\/p>\n<\/div><\/div>

From the very beginning, expectations for the knowledge and ability of artificial intelligence were high. For example, it was claimed that perfect machine translation would be completely possible within three to five years. Ten years later, that did not turn out to be the case. Because of these sky-high expectations that couldn’t be met – not just for machine translation, but for artificial intelligence in general – interest and investment in AI research declined sharply. A real ‘AI winter’ arrived, lasting from the 1970s to the end of the 1980s.<\/p>\n<\/div><\/div><\/div><\/div><\/div><\/div><\/section>

\"\"<\/div><\/div><\/div><\/div><\/div><\/div><\/section>

What is AI?<\/strong><\/h2>\n

In the introduction to this article, we questioned whether we are always talking about the same thing when we talk about ‘AI’. In the paragraphs that followed, we ourselves were guilty of using the term as a general denominator to name all kinds of technologies. Time to rectify that.
\nIn general, the term ‘artificial intelligence’ refers to all technologies that try to mimic human thinking and learning\u00b2. Whereas traditional computer programmes follow a fixed script to perform a specific task, AI systems use machine learning, learning from data containing relevant examples and recognising patterns in it. In other words, traditional computer programmes blindly and meticulously follow a roadmap, over and over again. AI, on the other hand, processes data and learns in the meantime to improve itself.<\/p>\n

AI in the translation industry<\/strong><\/h2>\n

AI is thus as complex as the human thinking it tries to emulate and has a wide range of applications by now. Hence, using the term as an umbrella term can be misleading and cause disappointment. It is therefore important to know which form of AI is best suited for particular tasks. Here are some examples of specific forms and AI applications used daily in the translation industry:<\/p>\n