[The following blog post was written by ChatGPT, based on the transcript which was also summarized by ChatGPT. It has not been carefully edited.]


The localization industry is witnessing a transformative shift with the advent of large language models (LLMs) like GPT-3 and GPT-4. As these AI-powered models continue to evolve, they are reshaping traditional workflows and presenting new opportunities and challenges. In this blog post, we’ll explore the impact of LLMs on the localization industry, discussing recent developments, use cases, and potential implications for professionals in the field, based on insights from ChatGPT in Localization II, Day 1, hosted by Custom.MT on April 27, 2023.

I. The Growing Importance of LLMs in Localization

The online event, ChatGPT in Localization II, aimed to discuss the latest developments in localization, particularly the implementation of LLMs in organizational workflows. The event featured panels with industry researchers, buy-side localization leaders, and experts in machine translation and quality estimation. Demos of translation tools integrating GPT-3 and GPT-4 were showcased, highlighting different use cases and scenarios. The event also included practical sessions, workshops, and a hackathon focused on tasks like inclusive language translation, content summarization, and creating marketing content.

II. Recent Developments and News

  1. Hugging Chat by Hugging Face: A new chatbot, Hugging Chat, offers free access to users and shares similarities with ChatGPT. The rise of chatbots presents promising opportunities for businesses and organizations in the localization industry to streamline customer service and create personalized user experiences.
  2. Newswire’s GPT-4 Integration: Newswire, a Canadian company, has integrated GPT-4 into their workflow for English to Quebecois French machine translation of press releases. This move demonstrates growing confidence in LLMs and their potential to handle specialized translations.
  3. Research on MTQE and Document-Level Machine Translation: The localization industry has seen a surge in research on machine translation quality estimation (MTQE) and document-level machine translation using LLMs. MTQE is crucial for ensuring that translations meet desired quality standards, while document-level machine translation aims to address context-related issues and provide more coherent translations across longer texts.
  4. Tencent’s Role-Playing Prompts: Chinese tech giant Tencent has been researching ways to enhance machine translation quality using role-playing prompts. By providing specific scenarios and contexts for translation tasks, models can generate more accurate and relevant translations.
  5. Mind Your Language’s ChatGPT Integration: Mind Your Language, an LSP based in Hong Kong and Singapore, conducted a case study where clients overwhelmingly requested the integration of ChatGPT into their human editing service. This illustrates the growing demand for LLMs in the industry and their potential to augment human translation services.
  6. Reddit’s Data Access Policies: Reddit is considering charging for access to their data downloading API, which could have repercussions for the language industry. Access to conversational data from platforms like Reddit is crucial for training LLMs and enhancing their capabilities. This potential shift in data access policies highlights the importance of developing alternative data sources and strategies.

III. Embracing the Potential of LLMs in Localization Amidst Uncertainty

The rapid advancements in LLMs and AI have created uncertainty within the localization industry, as professionals grapple with the potential impact of these technologies on their jobs and traditional workflows. The ChatGPT in Localization II event offered an opportunity for panelists and industry experts to discuss these concerns and provide valuable insights into how the industry can adapt to the changing landscape.

  1. Overcoming Uncertainty: Projects and budgets have been frozen due to the uncertainty surrounding the impact of LLMs and AI on the localization industry. Many professionals are unsure about their job security and are hesitant to embrace new technologies. However, panelists at the event emphasized the need to overcome this uncertainty by understanding the potential applications of LLMs and incorporating them into existing workflows.
  2. Paradigm Shift: The scale and capabilities of LLMs are now forcing a paradigm shift in the localization industry, which has historically been slow to adapt to new technologies. The integration of LLMs into productivity tools and translation management systems (TMS) is a significant development that can help drive this shift.
  3. Prompt Engineering: As LLMs continue to evolve, prompt engineering is emerging as a new skill for linguists to adapt to the changing landscape. This skill will be essential for professionals to effectively utilize LLMs in their work and ensure the best possible output.
  4. Addressing Enterprise Resistance: Enterprises have been resistant to change due to concerns about copyright, data privacy, and potential errors in output. However, the rapid advancements in AI and LLMs may force them to adapt. Panelists encouraged professionals to communicate the benefits of LLMs to stakeholders and demonstrate their value in enhancing the localization process.
  5. Industry Challenges: The localization industry faces several challenges when it comes to adopting LLMs and AI, such as having data in the right format, managing quality, and reinventing roles and processes to accommodate new technologies. Panelists highlighted the importance of staying informed, collaborating, and experimenting with LLMs to address these challenges and unlock their full potential.

IV. GPT Applications and Mindset Shift

  1. Potential of GPT for Localization: GPT can be utilized for various applications in the localization industry, including quality assurance, content creation, and customer-facing services. By understanding the potential of GPT, professionals can leverage this powerful tool to enhance their workflows.
  2. Empowering Tool: It is essential to view GPT as an empowering tool that can augment human capabilities, rather than a threat to the industry. Adopting this mindset can help professionals harness the power of GPT to create more efficient, high-quality, and personalized localization solutions.
  3. Involving Stakeholders: Involving all stakeholders, including linguists, in the process of adopting and adapting to new technologies is crucial. This collaborative approach can ensure the successful integration of GPT into localization workflows and help drive innovation in the industry.
  4. Testing and Experimentation: To identify the best use cases and applications for GPT in localization, it is essential to test and experiment with its capabilities. This approach can help organizations uncover areas where GPT can enhance existing workflows and deliver the most value.
  5. Medical Accuracy and Safety: When using GPT in the health domain, it is vital to ensure medical accuracy and safety. By focusing on these concerns, professionals can develop best practices and guidelines for using GPT in healthcare-related localization tasks.
  6. GPT Beyond Translation: It is important to explore GPT’s potential for non-translation localization tasks, such as editing source content, adapting translations for different audiences, and promoting language inclusion. This broader perspective can help unlock new possibilities for the localization industry.

V. The Evolution of LLMs and Their Impact on the Localization Industry

  1. Gradual Evolution: LLMs have been evolving gradually, and their growth has been driven by ongoing research and development in the field. Understanding the history of LLMs can help professionals appreciate the progress made in the industry and anticipate future advancements.
  2. Growth in Scale and Multilingual Capabilities: LLMs have been growing in scale and becoming more multilingual, allowing them to handle a wider range of languages and tasks. This development has significant implications for the localization industry, as it enables more accurate and efficient translations across diverse languages and cultures.
  3. Innovations in Prompting Mechanisms and Content Personalization: LLMs have introduced innovations in prompting mechanisms, allowing models to receive natural language prompts and perform specific tasks. This development, combined with the potential for content personalization, has opened up new possibilities for localization professionals.
  4. Importance of Getting Linguists on Board: To fully leverage the potential of LLMs, it is crucial to get linguists on board and help them see the technology as an enabler rather than a replacement for their work. By fostering a collaborative mindset, professionals can harness the power of LLMs to enhance the localization process.
  5. Developing Better Pricing Models and Processes: The industry needs to develop better pricing models and processes for working with LLMs to ensure that linguistic resources are properly valued and utilized. This approach can help create a more sustainable and efficient localization ecosystem.

VI. The Future of Translation with LLMs and NMT

  1. Hybrid Approach: The future of translation lies in a hybrid approach that leverages the strengths of both LLMs and Neural Machine Translation (NMT) technologies. By combining these tools, professionals can achieve more accurate and efficient translations.
  2. Evolution of Quality Estimation: Quality estimation is evolving into more advanced quality intelligence models that can detect and classify translation errors. This development enables more efficient human post-editing and automated post-editing processes, further enhancing the localization workflow.
  3. Shifting Human Roles: The role of humans in the translation process is shifting towards focusing on areas where their expertise is needed,

VII. Demos of GPT Integration and Applications

As part of the event, several companies showcased their demos of GPT integration and applications within the localization industry, illustrating the potential of LLMs to improve translation quality, efficiency, and customization.

  1. Localize.ai: Localize.ai demonstrated a contextualized translator that allows users to provide a short description for better translation results. They also showcased the integration of glossaries and the ability to generate target copy without any source text, highlighting the versatility of GPT in localization.
  2. Custom MT: Custom MT showed how to blend translation memory, glossary, and AI-generated translations to improve translation quality. They also demonstrated the use of prompt engineering to influence GPT’s output in real-time, illustrating the potential for fine-grained control over the translation process.
  3. Bureau Works: Bureau Works highlighted the seamless integration of glossary terms and translation memory with GPT-generated translations. They also showcased the use of AI for reviewing translations and identifying parts of speech, offering a glimpse into the future of AI-assisted quality assurance.
  4. Smartcat: Smartcat demonstrated the ability to create custom presets for GPT and use them in the translation editor. Users can craft their prompts and test the output in real-time, allowing for greater customization and control over the translation process.
  5. Terence’s Demonstration: Terence showcased an app designed as a gateway to Chat GPT, offering various features for translators, such as selecting models, adjusting temperature, importing documents, providing translation guidance, and more. The app allows users to translate, paraphrase, correct text, summarize, and ask GPT to perform free prompt tasks, like generating a menu in a different language. Users can also save outputs on their local disk. The app is available for purchase on mydutchpel.com, and ongoing development aims to enhance its capabilities, including the possibility of generating translation memories directly.

VIII. AI Actions and the Future of Localization

As AI continues to evolve, its potential applications within the localization industry become increasingly diverse.

  1. Customizable AI Actions: AI actions can be created and customized to perform various tasks, such as translation, text shortening, and rephrasing, offering a wide range of possibilities for localization professionals.
  2. Providing Tools to Customers and the Public: Companies within the industry can provide AI-powered tools to customers and the public, allowing them to access quality presets right from the start and further streamlining the localization process.
  3. Importance of Staying Updated: As the localization industry rapidly evolves, it is crucial for professionals to stay informed and adapt to changes, ensuring their skills and knowledge remain relevant.
  4. Connecting with Other Teams: Localization managers should connect with content strategy, digital strategy, and global engineering teams to ensure a holistic approach to localization projects, maximizing efficiency and collaboration.
  5. AI Applications in Various Areas: AI can be used for various tasks, such as market research, compliance, and creating test cases, making it a valuable tool for localization professionals to harness in diverse ways.
  6. Ensuring Ethical and Compliant AI Use: Localization professionals must work closely with legal and data officers within their organizations to ensure the ethical and compliant use of AI technologies, safeguarding user privacy and data security.
  7. The Future of Direct Authoring: As AI continues to advance, the future of the localization industry may involve more direct authoring in target languages, rather than relying solely on translation. This shift could lead to even greater efficiency and accuracy in the localization process.