Hello everyone!
Although this topic has been present for many years, as of late, we are talking more about it; especially after ChatGPT and other AI models have come out and become very popular. But what does this mean for translators?
There are several AI language models available in the market today, each with its unique capabilities, strengths, and weaknesses. Here are a few notable examples:
- GPT-3 (ChatGPT): OpenAI’s latest and most advanced language model, known for its ability to generate human-like language and perform a variety of language tasks.
- BERT: Developed by Google, BERT is a pre-training language model that excels in understanding the context of words and sentences.
- Transformer-XL: Another model developed by Google, Transformer-XL is designed for language modeling and has shown impressive results in generating coherent and fluent sentences.
- RoBERTa: Developed by Facebook, RoBERTa is a variant of BERT that has achieved state-of-the-art results on several natural language processing tasks.
- XLNet: Developed by researchers at Carnegie Mellon University and Google, XLNet is a novel language model that uses an autoregressive and autoencoding framework, leading to improved performance on several language tasks.
These are just a few examples, and there are many other language models out there with their unique strengths and weaknesses. Choosing the right one for a particular application depends on several factors, such as the desired task, dataset size, and computing resources available.

Let’s focus on ChatGPT for a moment, this is how it introduces itself:
“As an AI language model, my primary function is to process natural language input and generate natural language output. While there are several other language models available, there are a few key ways in which I am different from others:
- Flexibility: I am a highly flexible AI language model that can be fine-tuned for various natural language processing tasks, such as question-answering, language translation, summarization, and more. This flexibility makes me highly adaptable and suitable for a wide range of use cases.
- Training data: I have been trained on a vast and diverse corpus of text data, which includes everything from news articles and scientific papers to social media posts and conversational language. This training data helps me understand the nuances of natural language and generate more accurate and human-like responses.
- Continual learning: I have the capability to continually learn and improve based on feedback from users. This means that as more people interact with me and provide feedback, I can adapt and improve my responses to better meet their needs.
- Multilingual support: I support several languages and can translate between them, making me a useful tool for communication across different countries and cultures.
Overall, my flexibility, training data, continual learning, and multilingual support are just a few of the ways in which I am different from other AI language models.”
One of the most popular AI applications in the translation industry right now is machine translation (MT). MT is a technology that uses algorithms to automatically translate text from one language to another. It has become widely used in recent years, with platforms such as Google Translate and DeepL offering free online translations that are sometimes of reasonable quality.
However, it is important to remember that MT is far from perfect and has its limitations. While it may be suitable for simple, straightforward translations, it struggles with more complex texts, such as legal documents, literature, or technical manuals. This is because AI lacks the human intuition and cultural understanding necessary to accurately translate these types of texts. Moreover, MT cannot pick up on nuances or the context of the source text, which can lead to mistranslations and inaccuracies.
This is where human translators have a clear advantage over AI. Human translators can understand the nuances of the source language, recognize the context, and produce accurate translations that convey the intended meaning of the original text. Moreover, human translators can apply their own cultural knowledge and intuition to ensure that the translation is culturally appropriate for the target audience.
Therefore, it is highly unlikely that AI will ever completely replace human translators. Instead, it is more likely that AI will complement and enhance human translation work, making the process more efficient and productive.
For translators who want to learn to use AI to their advantage, there are a few steps they can take. First, it is important to stay up to date with the latest developments in AI and MT technology. This can be done by reading industry news, attending conferences and webinars, or participating in online communities and forums.
Translators can also experiment with different MT tools to find one that works best for them. Some MT platforms allow users to customize and train their own models, which can improve the accuracy and quality of translations. Additionally, some tools offer post-editing functionality, allowing translators to edit and refine MT output to ensure accuracy and readability.
Finally, translators can collaborate with AI developers and researchers to improve the quality and functionality of MT technology. By providing feedback and insight into the translation process, translators can help shape the development of AI tools to better serve their needs.

In conclusion, AI should not be seen as a threat to the translation industry, but rather as a valuable tool that can enhance and improve the work of human translators. While AI may never completely replace human translators, it can help make the translation process more efficient and productive. By staying up to date with the latest AI developments and experimenting with different MT tools, translators can learn to use AI to their advantage and improve the quality of their work.
I’ve been using ChatGPT for over a month now, and it helped me to write this blog. Yes, I input ideas to it about what I want to write, and it replies with a text that includes my ideas. I just copy and paste it on Word or directly on WordPress. I check it and make any necessary changes and, of course, I add “the human touch” to it.
I’ve also been using DALL E. This AI model generates images from any instructions you give it. Actually, the images used on this blog were generated by it.
So, what do you think about AI? Do you really think it can be a threat to translators? Or do you think it can be a very helpful tool? Let me know all about it in the comments, and don’t forget to subscribe!
Thank you to Day Translations for sponsoring this post! Make sure to click on the link to find out about the services they offer. They recently had their 16th Anniversary, so Happy Sweet Sixteen!
Until next time, take care and stay safe!
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