Ask ChatGPT – August 1, 2023

My Conversations with ChatGPT
Machine Translation (MT) and translations generated by AI have brought about a paradigm shift in the translation industry. The output of MT will continue to improve, especially when associated with clients’ translation memories and human editing. Language Service Providers are adapting and are including MT in their processes, when MT is applicable. While linguists will continue to be essential in the process, their role will shift from that of translators to validators of content generated by MT. At Excel Translations, we wanted to know what AI thinks about all of this and decided to have an open conversation on the matter with ChatGPT. I will regularly publish a question and ChatGPT’s response, uncensored.

QUESTION 37:

Is there a limit on how much content machine translation can handle?

Chat GPT’s Response:

As of my last update in September 2021, machine translation technologies have certain limitations on how much content they can effectively handle. These limitations arise from various factors:

1. Input Length: Many machine translation models process content in fixed-length segments or batches. If the content to be translated exceeds this limit, it may need to be divided into smaller parts, which can affect translation quality and coherence.
2. Memory and Processing Power: Machine translation models often require significant computational resources and memory to process large amounts of text. As the content size increases, the translation process may become slower or require more powerful hardware.
3. Contextual Understanding: Longer texts may contain more complex sentence structures, idiomatic expressions, and references to earlier parts of the text. Some machine translation models may struggle to maintain consistent understanding of context across long passages, leading to less accurate translations.
4. Quality vs. Speed Trade-off: Some machine translation systems prioritize speed over translation quality, especially for real-time applications like chat translation. Longer texts may face lower translation quality due to time constraints.
5. Domain Specificity: Machine translation models trained on general text might not perform as well on specialized domains with specific terminology or jargon. Translating lengthy texts in specialized fields can be more challenging.

It’s worth noting that the field of machine translation is constantly evolving, and researchers and developers are working on improving these limitations. Advances in neural machine translation (NMT), model architectures, and hardware capabilities may lead to improvements in handling larger content sizes and maintaining translation quality.

If you need to translate a substantial amount of content, it’s a good idea to evaluate different machine translation systems and assess their performance on your specific use case to determine their limitations and effectiveness for your needs. As of my last update, cloud-based translation services often have higher limits compared to free or consumer-grade translation tools, making them more suitable for large-scale translation tasks. However, the landscape may have changed since then, so it’s advisable to check with specific translation providers for the most up-to-date information.