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Generative Artificial Intelligence: A New Era in the Delivery of Language Services

These revolutionary AI systems are taking automated translation and localization to new heights. Even as this technology evolves, put it to work for you now.

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Lionbridge Embraces Generative AI Technology To Enable Customers To Augment Business Content

Position your enterprise to transition to this rapidly evolving technology with Lionbridge’s expert guidance. 

Although computer scientists have been following developments in generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) for years, the technology grabbed the mainstream’s attention with the 2022 launch of ChatGPT, an LLM developed by U.S. tech company OpenAI. Reuters® reported that the novel app was the fastest-growing app in history, attracting an estimated 100 million users two months after its launch.

Generative AI technology is receiving attention for a good reason; its ability to generate text in pretty much any language will profoundly change how we work and conduct business.

Goldman Sachs estimates the tool could be responsible for an almost $7 trillion increase in global Gross Domestic Product (GDP) and raise productivity by 1.5 percent by 2033.

As this groundbreaking technology evolves and becomes scalable, it will disrupt the localization industry. This AI is already impacting the delivery of language services.

Lionbridge is an early adopter of generative AI technology and is poised to help you leverage all it offers.

Defining the Landscape

You’re bound to come across terminology associated with generative AI. Here’s what you need to know to get started.

What is Generative AI?

It’s an Artificial Intelligence (AI) system that can generate novel content, including text and images, based on prompts and extensive multimodal training. It determines the most plausible output that appears to have been produced by a human.

What is a Large Language Model?

It’s an AI system focused on languages. It can summarize, translate, predict, and generate text from knowledge gained from massive databases. Although it’s not specifically trained to translate text, it can do so with decent quality and is quickly improving.

What is GPT?

It’s a family of Large Language Models created by OpenAI. The GPT family includes various versions of the AI, such as GPT-3, GPT-3.5, GPT-4, and others.

GPT-3.5 and GPT-4 power ChatGPT, OpenAI’s freemium chatbot product. GPT-4 is recognized as the most capable of all Large Language models and produces, among other things, better linguistic results.  

Other LLM brands include Google’s Bard, PaLM and LaMDA, Meta AI’s LLaMA 2, and DeepMind’s Chinchilla. Many other models exist or are in development.   

Large Language Model and Generative AI Technology On-Demand Webinar

Find out how this Artificial Intelligence will affect localization workflows. Discover new possibilities for translation and content creation.

Generative AI Across the Content Lifecycle

There are opportunities to leverage generative AI, even in its early stages, but you must use caution when deploying it.

When Should Generative AI Be Used?

During Content Creation

The technology can create content when you have references and examples. For instance, generative AI can help you create a new marketing campaign based on a prior campaign and help you check your content for grammatical or stylistic changes.

During Initial Translation

If you are performing multilingual content generation, generative AI will be excellent at creating multilingual prompts because it will have source input and output to use as a reference.

During Post-editing and Content Review

The technology is excellent at comparing content across languages to determine whether it has the same meaning. It can edit the text for a better fit when necessary. When considering whether to use generative AI instead of linguists for some of these tasks, make sure the language pair and domain work well with generative AI and that it is more cost-effective than using the services of a linguist. Our initial research suggests that some use cases will be more suitable for generative AI, and others will be more suitable for linguists.

When Shouldn’t Generative AI Be Used?

During Content Creation

Don’t use generative AI to create content when you cannot provide context. The technology cannot determine whether something is true and could make incorrect assertions. For instance, it’s not a good option when producing technical documentation.

During Initial Translation

The technology is not a replacement for Machine Translation and should not be used as such for initial translations. Current generative AI models are not economically efficient.

During Post-editing and Content Review

The technology was largely built from an English corpus of publicly available content and is, therefore, less able to determine the context of the text in highly specialized domains or provide quality reviews in less common languages. We expect improvements to these shortcomings in the future, but until such time, we recommend using a blended model that incorporates both generative AI and linguists.

Put Generative AI To Work for You With These Services

Generative AI technology has yet to mature fully. GenAI providers need to scale their servers before companies can use the technology for industrial localization. However, we can leverage it for certain content creation, translation, and post-editing tasks. 

Lionbridge uses generative AI to maximize internal automation and bolster our customers’ business content. We can evaluate LLMs, clean and annotate data for LLMs, and help identify and root out stereotypes, biases, or problematic content.  

We are continuously researching and developing ways to incorporate LLMs into professional translation and can help you get the most out of it as it rapidly evolves. Let us help you get started via the following offerings:

Content Remix: Multilingual Text Generation or Transcreation

This offering is a self-service platform to generate multilingual content from initial information and have it reviewed by specialists from the Lionbridge Crowd. It provides a user interface for LLM-generated content writing for particular use cases and is suited for companies seeking to:

  • Produce creative, engaging multilingual content from scratch, including product descriptions, tweets, and other material based on data your company already possesses.
  • Generate localized content from existing domestic source text that will resonate with the target audience, even if the result does not strictly adhere to the source.
  • Adapt scripts to meet time constraints, as LLMs are good at shortening translations while preserving meaning.

Prompt Engineering

This service focuses on effective, prompt input to improve the quality of GenAI output. 

Lionbridge offers simplified, prompt engineering solutions via backend development. We help customers curate the type of content they use as examples for the engines and engineer prompts to improve the translation performance of LLMs in real production scenarios.

Simplified prompt engineering enables the user to iterate through variations quickly and select the best output. High-performing prompts may be saved and deployed on similar content for either LLM text generation or translation tasks before a professional gets involved in the project. 

We offer:

  • Prompt creation, translation, transcreation, translation review, analysis, and testing
  • Response evaluation and validation. 

Optimization of Multilingual Assets

This service uses LLMs to modify linguistic assets, such as Translation Memories (TMs) and stylistic rules. 

Want to informalize your entire Translation Memory (TM), adapting the tone and style to your specification? With generative AI, you can achieve this goal more affordably than was previously possible.

Post-Editing and Improvements to Localization Workflows

This offering uses LLM technology to support post-editing. 

Having the LLM system perform the most repetitive and common post-editing corrections significantly reduces the human editor’s workload. It makes the whole translation workflow easier, faster, and more cost-effective. 

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Meet Our Generative AI Experts

Vincent Henderson

As Lionbridge’s leader of the product and development teams, Vincent focuses on ways to use technology and AI to analyze, evaluate, process, and generate global content. He is especially attentive to the disruption of content products and services brought about by Large Language Models.

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Rafa Moral

As Vice President, Innovation, Rafa oversees R&D activities related to language and translation. His responsibilities include initiatives involving Machine Translation, Content Profiling and Analysis, Terminology Mining, and Linguistic Quality Assurance and Control.

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