LANGUAGE:
LANGUAGE:
Content Services
- Technical Writing
- Training & eLearning
- Financial Reports
- Digital Marketing
- SEO & Content Optimization
Translation Services
- Video Localization
- Software Localization
- Website Localization
- Translation for Regulated Companies
- Interpretation
- Instant Interpreter
- Live Events
- Language Quality Services
Testing Services
- Functional QA & Testing
- Compatibility Testing
- Interoperability Testing
- Performance Testing
- Accessibility Testing
- UX/CX Testing
Solutions
- Translation Service Models
- Machine Translation
- Smart Onboarding™
- Aurora AI Studio™
Our Knowledge Hubs
- Positive Patient Outcomes
- Modern Clinical Trial Solutions
- Future of Localization
- Innovation to Immunity
- COVID-19 Resource Center
- Disruption Series
- Patient Engagement
- Lionbridge Insights
Life Sciences
- Pharmaceutical
- Clinical
- Regulatory
- Post-Approval
- Corporate
- Medical Devices
- Validation and Clinical
- Regulatory
- Post-Authorization
- Corporate
Banking & Finance
Retail
Luxury
E-Commerce
Games
Automotive
Consumer Packaged Goods
Technology
Industrial Manufacturing
Legal Services
Travel & Hospitality
SELECT LANGUAGE:
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.
You’re bound to come across terminology associated with generative AI. Here’s what you need to know to get started.
The current Neural Machine Translation (NMT) paradigm is ending. A new paradigm will replace it, likely based on Large Language Models. As this development materializes, you can expect the following outcomes:
Reduced translation costs
Greater productivity and the ability to generate content at greater scale
Improved translation quality — text that appears to have been written by a human
Enhanced customer experience
New opportunities to enter more markets
There are opportunities to leverage generative AI, even in its early stages, but you must use caution when deploying it.
While generative AI technology has yet to mature fully, we can leverage it for certain content creation, translation, and post-editing tasks.
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.
Do you still have questions about generative AI? Here are the answers to some of the questions our customers frequently ask.
Generative AI and LLMs like GPT are AI engines that have learned how humans write text. They’ve been trained on the massive corpus of the internet. Give the model an input, and it will produce the most plausible output from its extensive training.
It is appropriate to use LLMs for all types of content when engaging in the following tasks: editing, error correction, management of style and tone, terminology adherence, and clarity of expression.
Use LLMs when your content requires fluency to produce reach and engagement. Using LLMs for content requiring precise translations is riskier as this technology can produce inaccurate information.
We discovered that OpenAI’s GPT-4 model can produce better translation results than Yandex in certain situations for the English-to-Chinese language pair. This achievement is a significant milestone. However, GPT-4 doesn’t yet deliver the same outcomes as the established NMT engines (Microsoft, Yandex, Google, DeepL, and Amazon) and can be 12-50 times more costly.
Older GPT models, such as ChatGPT and GPT-3, are less advanced than GPT-4, and their translation performance is inferior to the major, specialized NMT engines. We found some issues with agreement and concordance of gender that are not present in NMT outputs.
LLMs are in great demand, but they cannot yet cater to the volumes of content needed for industrial-scale localization. We expect this situation to change, but the timing is uncertain. Until such time, it will take longer to process translations and generally cost more to use LLMs for translations instead of NMT engines.
It is imperative to review and understand the terms of use and privacy policy of the LLM you intend to use, especially free offerings. Typically, when using free technology, your information is the price you pay.
The National Cyber Security Centre outlines some risks and recommends that you refrain from providing sensitive information to public LLMs and avoid submitting queries to public LLMs that could harm your company should they become public.
Lionbridge goes to great lengths to protect its customers’ information when using automated technology.
The pace at which LLMs are improving suggests these AI systems are advancing the Natural Language Processing (NLP) field and will be part of a new paradigm as the Neural MT paradigm ends. Nonetheless, it is too early to entirely dismiss the major MT engines for automated translation.
During this transition period, we advocate using a hybrid model combining the benefits of both NMT and LLM engines rather than selecting one model at the exclusion of another.
A promising area of our research demonstrates the benefit of a hybrid model that uses an NMT engine for translations and then leverages an LLM engine for post-editing. This approach improves the fluency of the NMT output since LLMs have the uncanny ability to produce text that appears to have been created by humans.
Generative AI has the potential to resolve some longstanding quality issues associated with Neural MT engines, including its inability to attain and consistently achieve the right formality level, tone, or handle negation.
As generative AI and LLMs mature, expect:
A significant leap in MT quality, including enhanced workflow automation
Increased global content generation and output
Greater adoption, and
Enhanced customer experience through MT use
Lionbridge can — and has — provided the following LLM-related services for its customers:
Multilingual text generation / transcreation
Prompt engineering / multilingual prompt engineering
Prompt creation, translation, transcreation, translation review, analysis, and testing
Response evaluation and validation
Diversity, equity, and inclusion initiatives, including identification of stereotypes, biases, or problematic content in the training corpus, prompts, and responses
Reinforcement learning from human feedback (RLHF)
LLM evaluations
Data-related services, such as data annotation and data cleaning for LLMs
Multilingual asset optimization
Model fine-tuning / customization
Workflow automation
Our Research & Development (R&D) team continuously investigates new ways to deploy generative AI as it evolves.
No, generative AI will not replace Language Service Providers (LSPs). Since its inception over 25 years ago, Lionbridge has embraced, become an expert on, and fully leveraged emerging technologies to provide top-notch language services. Our ability to adapt to technological change has driven our growth, longevity, and success. When assessing LSPs, it is imperative to investigate the supplier’s ability to capitalize on evolving technologies.
During this transition period, it may be premature to change the usage of your current MT engines drastically; our vast MT experience makes us suited to help you identify the right moment to perform that change and provide guidance on execution.