Everything you need to know about machine translation

This article has been updated as of April 2025

Using machines to translate content from one language to another has long been a goal for computer scientists and translators. About ten years ago, machine translation made its first great leap forward, thanks to the practical application of techniques such as machine learning and neural networks.

What is machine translation?

Machine translation refers to the use of intelligent software and technology to translate texts from one language to another without the need for human intervention. Originally, these systems were based on rules that used grammatical structures and bilingual dictionaries.

Over time, statistical systems were developed to achieve a faster and more accurate process. These were based on the analysis of enormous amounts of human translations and the subsequent use of statistical methods to generate a translation result.

Today, neural translation systems are based on neural networks and deep learning to achieve an automated continuous learning model and very high-quality results.

In fact, a study published last month by CSA Research (2022) predicts that current trends in artificial intelligence development will result in machine translation that can fully and adapt translations in a receptive way based on context, metadata and usage scenarios. This prediction came true in late 2024 with AI Translation, the latest evolution using deep learning and advanced contextual understanding.
  

Machine translation

Machine translation (MT)

Machine translation refers to a purely automated translation system capable of converting source content into target languages in a matter of seconds.

Let's take the example of Google Translate: this platform is able to instantaneously translate texts through the use of algorithms and patterns extracted from millions of samples.

This type of machine translation allows companies to translate more and more content without having to add resources to manage the translation process.

Machine translation goes far beyond converting words from one language to another. At Pangeanic, when we speak of machine translation, we are referring to a process adapted to each context which improves machine translations based on human revisions, interpretations and corrections.

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The Advantages of Machine Translation

Machine translation and its ability to implement a first stage of purely automated translation brings many positive aspects to any project requiring translation services. And the fact is that, as far as speed, volume and cost are concerned, MT has far surpassed human translators' capabilities. The following are some of the main advantages.

Immediacy and Efficiency

For large quantities of texts, machine translation provides a first layer of automatic translation that will speed up the translation process and it will allow organizations to save enormous amounts of time and money.

To ensure the accuracy and quality of professional translations, let's remember that it is necessary to have a professional translator to review the resulting translation, as well as verify and edit any inaccurate information.

In this way, machine translation tools enhance the value of the human experience and skills, freeing the translator from the most tedious part, and allowing them to focus their work perfecting the translations.

Feasibility and Scalability

Over the years, the language industry has heavily invested in technological developments that have made translation more accessible and can serve a wider audience, without compromising the quality of the results.

Machine translation may therefore be a very viable option from a financial point of view. If a professional translator is hired to work on the translation from scratch, the resulting bill is likely to be sky-high.

Automation offers the translation tools necessary for the system to constantly evolve without having to add more investment and resources as the volume of content to be translated increases.

Content Management

Machine translation can simplify the entire workflow by automating the process of content management tasks so that linguists and companies don't have to worry about managing ongoing translations, reducing the workload.

Intelligent automation empowers users with the ability to manage and update translations automatically in the same connected space. This is especially useful when linking actions to tasks, validating translations or corrections, or viewing active translations.

Privacy

Remote working due to COVID-19 has increased the costs in security breaches, at USD 1.07 million, according to an IBM report published this year.

An automated translation process involves fewer contact points and a shorter transit time, so fewer people are likely to gain access to private data. As a result, machine translation provides organizations with greater control on data governance.

In addition, some machine translation tools, such as anonymization, allow sensitive or confidential content to be translated in a way that preserves personal data and protects the company's privacy and reputation.

Flexibility and customization

Deep analysis tools can use drafts that provide machine translators with previously used phrases and concepts, taking advantage of a “translation memory” that can be customized for each specific user.

Depending on the exact content or its priority, machine translation can perform different quality controls, such as glossary compliance or numerical consistency checks.

These options are just examples of the flexibility and customization that machine translation provides for each individual organization.

Read more: Languages that defy machine translation

The Evolution from Machine Translation to AI Translation

While traditional machine translation has served us well, AI translation represents a revolutionary shift in language processing technology.

Understanding the Key Differences

The transition from statistical models to neural networks revolutionized translation quality. Now, advanced AI translation leverages Deep Adaptive AI Translation techniques that combine:

• Vector space representations of terminology and style preferences
• Agentic verification systems
• Quality estimation and control
• Sophisticated learning algorithms that continually improve performance

The Future of AI Translation

Research in AI translation continues to advance, focusing on refining neural networks to deepen AI's understanding of linguistic nuances and cultural contexts. Future developments may include:

• Greater adaptability to specialized fields like legal, medical, and technical translations
• Seamless integration with other technologies
• Improved real-time translation capabilities
• Enhanced support for low-resource languages

Greater adaptability means more specialized translation models in fields such as legal, medical, and technical translations. These areas often require precise terminology and an understanding of context that goes beyond mere word-for-word translation. AI systems are being trained to recognize and process the specific jargon and conventions used in these fields, which will lead to more accurate and reliable translations. For instance, in the medical field, AI could help translate patient records or medical research papers, ensuring that critical information is conveyed correctly across languages.

For seamless integration of AI translation with other technologies, imagine a world where AI translation tools are embedded in everyday applications, from video conferencing software to customer service chatbots. This integration would allow for real-time translation during conversations, breaking down language barriers and facilitating smoother communication in global interactions. As businesses expand internationally, the demand for such capabilities will only increase, making AI translation an essential tool for global commerce.

Improved real-time translation capabilities are now on the horizon. Until recently, systems struggled with context and idiomatic expressions, leading to awkward or inaccurate translations. Future advancements will likely focus on enhancing these systems to provide translations that are not only immediate but also contextually relevant. This could revolutionize how we communicate across languages, making interactions more fluid and natural.

Finally, there is a growing emphasis on enhancing support for low-resource languages. Many languages lack sufficient data for AI training, which limits the effectiveness of translation tools for speakers of these languages. By developing methods to better support these languages, AI translation can become more inclusive, allowing speakers of all languages to benefit from technological advancements.

The Role of Human Translators in the AI Era

Even with advancing AI technology, human translators remain essential. They provide cultural and contextual insights that enhance AI outputs, ensuring translations are not only accurate but culturally appropriate. The future lies in collaboration between human expertise and AI efficiency, allowing translators to focus on creative and complex tasks. While AI can handle basic translations and even some complex tasks, it often lacks the cultural and contextual insights that only a human can provide. Language is deeply intertwined with culture, and nuances such as humor, idioms, and emotional tone can be challenging for AI to grasp fully.

Human translators bring a wealth of world knowledge and experience that enhances AI outputs, ensuring that translations are not only accurate but also culturally appropriate. These adaptations many times require constant updates to real-world events. For example, a human translator can recognize when a direct translation might be offensive or misleading in a particular cultural context and can adjust the translation accordingly. This level of understanding is crucial in fields like marketing, where the success of a campaign can hinge on the subtleties of language.

The future of translation lies in collaboration between human expertise and AI efficiency and how AI makes us humans control the process. That is why we talk about "humans in control" and not "humans-in-the-loop" at Pangeanic. Translators will control the translation process with tools, not act as mere post-editors correcting machine mistakes. As AI takes on more routine and straightforward translation tasks, human translators will be freed to focus on more creative and complex assignments. This partnership can lead to improved quality in translations, as human translators can leverage AI tools to enhance their work while still applying their unique insights and skills.

Form a cutting-edge partnership for your translations 

Pangeanic's machine translation models are pioneers in the language industry. So much so, that several government agencies in the United States and the European Union, international organizations and corporations have chosen our translation models for their high-volume translation needs.

Pangeanic's approach combines the highest levels of flexibility, control, AI customization and user service with state-of-the-art technology to provide accurate, near-human machine translation. Want to try our technology? Talk to us or, better yet, request a demo.