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The Relevance of Machine Translation Amid a Generative AI World

Legacy translation engines are essential to AI-powered translation solutions to achieve cost savings and speed.

Tempted To Retire Machine Translation? Not So Fast.


Machine Translation tools continue to benefit enterprises that effectively incorporate them into their AI-driven translation workflow even as generative AI thrives.

The role of Machine Translation is unequivocally changing. Generative AI (GenAI) / Large Language Models (LLMs) will likely replace this legacy technology. The signs are clear:

    —LLMs are challenging MT engines with their superior contextual understanding.

    Generative AI solutions are proliferating.

Despite these developments, LLMs are not the new MT — at least not yet. GenAI cannot match the translation speed and affordability of top Neural Machine Translation (NMT) engines.

Given that LLMs are currently an unsuitable substitute for MT, how can you best leverage all available technologies to optimize your translation workflow and translate more content faster — as cost-effectively as possible — to enhance global outreach?

You may use the best of both technologies strategically, leveraging MT tools for a new LLM world.

    —Use MT for initial translations at the beginning of the process.

    —Use LLMs for post-editing and quality assurance tasks to enhance overall quality.

Combining MT and LLM technologies with human oversight enables enterprises to achieve desired translation results.

Connecting the World: How Diverse Technologies and Human Excellence Enhance Global Communication

Lionbridge executes four key steps as part of its cutting-edge translation services to produce the translation outcomes required by today’s enterprises.

The technological elements involve a combination of Machine Translation and generative AI, including our proprietary, state-of-the-art AI localization platform, Lionbridge Aurora AI™. A human in the loop is equally important to the process.

Our video explains how Lionbridge’s expert translation methods produce globally resonant content at unprecedented volume and pace.

The Benefits of Machine Translation as Its Role Evolves

Incorporating MT in your AI toolset and implementing it as the first translation pass enhances efficiency, resulting in the following benefits.

Cost Savings

MT reduces human translation hours, cutting costs and freeing up humans for important oversight work.

Faster Turnaround Times

MT processes translations at speeds unmatched by human and LLM capabilities.

Greater Scale

MT handles large volumes of content effortlessly.

Learn more about Lionbridge’s automated solution, Smart MT™, to Localize everything™.

What Is the Best Machine Translation?

Learn which Machine Translation engine will be most effective for your use case with Lionbridge’s Machine Translation Tracker. 

Selecting the right MT engine to meet your needs is challenging. The quality of your source content, source language, and target languages are among the factors that can influence MT engine performance. Lionbridge’s Machine Translation Tracker — the longest-standing measurement of the major MT engines — helps you select wisely. It measures the overall performance of an array of MT engines, as well as outcomes specific to language pairs and various topic domains. It now also tracks the performance of several LLMs for reference.

How AI-Powered MT Supports Major Verticals

Machine Translation can help overcome business challenges in any industry. See how our MT and AI solutions support legal, life sciences, and e-commerce customers.

Legal

Global legal cases may generate high volumes of multilingual legal eDiscovery documents that must be translated quickly. They may also require more official, high-level documents for court submission, etc. Learn when Machine Translation can translate legal documents accurately, efficiently, and cost-effectively.

Life Sciences

While AI must be used in a way that controls risk and protects end users and compliance, it's also a key tool for providing life sciences language services at scale. AI-supported, expert-led language services help companies involved in drug and medical device development meet tight deadlines, manage increasing documentation volumes, and enter new markets. Discover how MT and AI are helping life sciences companies create better patient outcomes. 

E-commerce

E-commerce is a critical way for companies to reach global markets. AI-enhanced MT can help these companies create a faster, steadier stream of engaging and personalized content for customers — regardless of their language. Learn how retailers have already been using MT and AI to connect with customers worldwide.

Dig Deeper Into Content About Automated Translation

Smart MT™: Enterprise-Grade Machine Translation + AI

Discover Lionbridge’s enterprise-grade Machine Translation and AI solutions that utilize the best MT engines and AI reviews for enhanced global communications.

Lionbridge Debuts Lionbridge Aurora AI™, the AI-Powered Orchestration Platform for Global Content Management

Find out how Lionbridge has augmented its offerings with a translation management system that optimizes workflow automation at scale for localization and beyond.

Lionbridge’s TRUST Framework to Build Confidence in AI Use

Achieve confidence when implementing generative AI into your language solutions with Lionbridge’s TRUST framework.

Case Study: How Lionbridge Improved Employee Engagement at a Large Aerospace Technology Provider

Gain insight into how Lionbridge’s Smart MT solution provided fast, efficient, and accurate translation for our client, leading to improved global employee engagement.

Language Ranking Based on Machine Translatability for More Effective MT

Consider language complexity before deploying Machine Translation. Our machine-translatability ranking will help support your business decisions.

Machine Translation in Translation

Stay updated on the important terms associated with Machine Translation with this handy cheat sheet.

Meet Our Machine Translation and Generative AI Experts

With deep AI expertise, you can feel confident about Lionbridge’s Machine Translation services and generative AI language services.

Rafa Moral

Vice President, Innovation 

Rafa oversees R&D activities related to language and translation, including initiatives pertaining to Machine Translation, Content Profiling and Analysis, Terminology Mining, and Linguistic Quality Assurance and Control.

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Vincent Henderson

Head of Product Language Services

Vincent leads the product and development teams at Lionbridge. He 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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A Brief History of Machine Translation

1954 - Georgetown researchers perform the first-ever public demonstration of an early MT system.

1962 - The Association for Machine Translation and Computational Linguistics is formed in the U.S.

1964 - National Academy of Sciences forms a committee (ALPAC) to study MT.

1970 - The French Textile Institute begins to translate abstracts using an MT system.

1978 - Systran begins to translate technical manuals.

1989 - Trados is the first to develop and market translation memory technology.

1991 - The first commercial MT system between Russian, English, and German-Ukrainian is developed at Kharkov State University.

1996 - Systran and Babelfish offer free translation of small texts on the web.

2002 - Lionbridge executes its first commercial MT project using its rule-based MT engine.

Mid 2000s - Statistical MT systems launch to the public. Google Translate launches in 2006 and Microsoft Live Translator launches in 2007.

2012 - Google announces that Google Translate translates enough text to fill 1 million books every day.

2016 – Both Google and Microsoft enable Neural Machine Translation (NMT), slashing word order mistakes and significantly improving lexicon and grammar.

2020 - As of October, Google Neural Machine Translation (GNMT) supports 109 languages.

2022 - Lionbridge experts share findings that MT engine output performance is stagnating, and all tracked engines perform similarly. These developments indicate that the Neural MT paradigm may be reaching a plateau and suggest that a new paradigm shift could be approaching.

2022 - OpenAI launches its generative AI engine, ChatGPT, to the public in November, highlighting an evolving and expanding translation technology landscape.

2023 - GenAI proliferates with more model launches, a steady stream of new iterations, and solutions catering to various industries and use cases.

2024 – MT’s relevance shifts, complementing LLMs as generative AI flourishes.

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