Discovering the Power of ChatGPT-4: A Game-Changer for Translating My Thriller Series
Embarking on an unexpected journey with ChatGPT-4, I uncovered its potential to revolutionize the way I translate my German texts into English.
A few days ago, after gaining access to ChatGPT-4, I didn’t immediately know what to do with it. Then, by chance, DeepL, the program I use to translate German texts into English, experienced performance issues one day.
So, I quickly switched to ChatGPT to see if the program could also produce decent translations.
I was more than shocked by the result.
DeepL is already a very impressive translation program, but ChatGPT did an even better job. It takes longer for the translation, but in return, it seemed much better to me. ChatGPT even mastered idioms and ambiguities without any issues. Of course, I wanted to know how this could be possible, so I asked ChatGPT the following question.
I noticed that you produce better translations than the market leader DeepL. How do you do that?
Thank you for the compliment! As an AI model, ChatGPT is based on the GPT-4 architecture developed by OpenAI. GPT-4 is an evolution of earlier models and has learned from an even more extensive corpus of text. There are several factors that contribute to ChatGPT potentially providing better translations than other translation services like DeepL:
- Extensive training: ChatGPT has been trained on a huge amount of text from various sources. This allows the model to develop a better understanding of language, context, and meaning.
- Context understanding: GPT-4 has a better understanding of context, enabling it to provide more accurate translations, especially when the text is ambiguous or idiomatic.
- Neural network architecture: The Transformer architecture that GPT-4 is based on allows the model to better capture complex relationships and dependencies between words in sentences.
- Continuous improvement: OpenAI continuously works on improving and advancing its models. Therefore, ChatGPT benefits from the latest advances in AI research.