Generative AI for Translation in 2024

In 2023, the landscape of Generative AI (GenAI) for translation saw remarkable advancements, prompting us to conduct an in-depth analysis beyond our annual State of the Machine Translation report. Our study, featuring a rigorous comparison between nine large language models (LLMs) from leading AI developers like Anthropic, Google, and OpenAI, and eight specialized Machine Translation (MT) models, unveils critical insights into the evolving capabilities of GenAI in translation.

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Key Findings:

• Performance & Quality: LLMs, while slower, are closing the gap in translation quality compared to specialized MT models, especially in general domain translations. Google’s PaLM 2 models (text-unicorn, text-bison) showed promising results, with text-unicorn ranking highest in general domain translations.
• Domain-Specific Insights: In specialized fields like Legal and Healthcare, traditional MT models still lead, highlighting the tailored efficiency of specialized systems.
• Cost-Efficiency: Generative AI models offer a cost-effective alternative for translation, with Google’s LLMs and LLaMA-2 being 20–25 times cheaper than traditional MT models. However, the slower speed of LLMs is a notable drawback.

For a detailed dive into our methodology, comparative analysis, and nuanced insights into the strengths and weaknesses of each model, visit our new blog. Join us as we explore the forefront of machine translation technology, shedding light on the intricacies of generative AI’s role in breaking language barriers.