Over the past decade, everyone in the translation industry has crossed paths with what we call machine translation. In the early days, linguists were cautious, and not without reason. But what exactly is machine translation? How is it different from human translation? And how does it compare to the AI-powered translation tools taking over the industry today? Let’s break it down.
A brief look back
The story begins in the 1950s, when the U.S. Department of Defense funded one of the first machine translation projects. Soon after, in 1954, IBM and Georgetown University ran what became known as the Georgetown–IBM Experiment – a historic demonstration of automated translation.
More than sixty sentences were translated from Russian into English, covering topics like politics, law, math, and science. The operator running the program didn’t even know Russian, yet the English translations came out printed and ready. The system worked with just six grammar rules and a vocabulary of 250 words – primitive by today’s standards, but revolutionary for its time.
What we mean by “machine translation”
In simple terms, machine translation (MT) refers to computer systems that perform translation, with or without human input. While the goal is always to achieve high-quality output, in practice, human linguists still need to step in and edit the results.
The kinds of mistakes MT systems make are quite different from human ones: wrong prepositions, articles, pronouns, or verb tenses. That’s why post-editing machine translation has become a standard in the industry – a necessary step to fix those machine-specific quirks. At Formula F, we’ve been in translation and localization long enough to see this shift firsthand. Our translators know the ins and outs of machine-generated text in their native languages and can fine-tune any machine translation into a polished, natural result. You can learn more in our Services section — or request a Quote if you need machine translation post-editing.
Enter artificial intelligence
If we think of machine translation as a tool for translators and a cost optimizer for clients, where does AI translation fit in? And how is it different?
AI has completely transformed nearly every industry. And translation is no exception. Artificial intelligence, at its core, is the ability of a machine to demonstrate human-like learning and reasoning. Unlike traditional rule-based MT programs, AI translation uses advanced models such as Neural Machine Translation (NMT).
Instead of relying on lists of words and strict grammatical rules, NMT works through neural networks – systems inspired by the way the human brain processes information. Rather than substituting one word for another, it tries to understand the context and produce a translation that sounds naturally fluent in the target language.
Sounds amazing… but is it flawless?
Not quite.
Even the most advanced AI systems struggle with cultural nuances, idioms, or texts that depend on historical or emotional context. The result may sound smooth and convincing… sometimes too smooth, but subtle errors can lurk beneath the surface.
That’s why blind trust in AI-generated translations can be risky, especially with sensitive content like legal, medical, or safety documentation. Increasingly, we’re seeing AI Assisted Translation with Human Revision projects, where expert linguists ensure that the final product truly reflects the meaning, tone, and intention of the original.
So where does that leave us?
At the end of this “review of the machines,” one question remains: where does the human stand in all this?
For us, the answer is clear: humans remain at the heart of the translation process. Machines are wonderful assistants, tireless learners that help us work faster and smarter. But will they ever truly understand the world, and the meaning behind every word, the way humans do?
Only time will tell.
