What is AI Translation?

We have been surrounded by AI for some time now. Think about the GPS you bought in 2010 to travel across the country. Consider the robot vacuum that cleans your kitchen. Also, there's the facial recognition you use to unlock your phone.

We sometimes think of AI as an undefinable, complicated super-tool. It doesn't always have to look like JARVIS from Iron Man, building suits and controlling an entire home.

The Evolution of AI

Artificial Intelligence (AI) started in the 1940s. However, AI research really grew in the 1950s and 1960s. Early AI research focused on creating algorithms for problem-solving using symbolic reasoning. However, progress was slow. This was due to limited computing power.

In the 1980s, a new approach to AI called "machine learning" emerged, which allowed algorithms to learn from data instead of being explicitly programmed. This approach led to breakthroughs in areas such as speech recognition, computer vision, and natural language processing.

In the 1990s and 2000s, the rise of the internet and the availability of large datasets fueled the development of machine learning algorithms that could handle massive amounts of data. This led to deep learning, a part of machine learning. It uses neural networks to learn different levels of data.

Interest in AI has grown recently. This is because of better deep learning techniques, more powerful computers, and the availability of large amounts of data.

Now in the 2020s, AI tools like ChatGPT are becoming widespread. ChatGPT is being adopted and tolerated as a machine translation tool. As the ways we use artificial intelligence grow, the quality and accuracy of translations will improve.

What are the Benefits of AI Translation for Businesses?

AI translation has quickly developed congruently with other general AI technology. The global investment in artificial intelligence grew from $12.75 billion in 2015 to $67.8 billion in 2020. Similarly, the machine translation market is continuing to grow by approximately 19% every year.

AI translation can help you translate your website and achieve your goals more easily. For instance, AI translation helped eBay increase its sales by 10.9%. This is possible thanks to AI powered translation. By automating translation, businesses can:

Reach a Wider Audience: With the help of AI translation, businesses can easily translate their content into multiple languages, making it accessible to a wider audience. This can help businesses to expand their reach and increase their customer base.
Save Money: AI translation reduces human translation costs, typically the most expensive part of website translation.
Get Faster Turnaround: AI translation can be done much faster than human translation, allowing businesses to quickly translate their content and respond to market demands in a timely manner.
Serve Customers Better: By translating their content into multiple languages, businesses can provide a better customer experience for their multilingual customers. Customers prefer product information in their own languages. 76% like to shop in their language, and 40% won’t buy from a site that uses a different language. This can help to build trust and loyalty among customers.
Gain Competitive Advantage: Businesses that are able to offer content in multiple languages have a competitive advantage in global markets. AI translation helps businesses quickly translate their content, giving them an advantage over competitors who cannot provide translations.

In summary, AI translation can help businesses to expand their reach, save money on translation costs, improve efficiency, and provide a better customer experience. This can ultimately lead to increased sales and a stronger position in the global market.

Learn about how Adaptive Translation™ can get you all these benefits

Types of AI Translation Technologies

Statistical Machine Translation (SMT)

Statistical Machine Translation (SMT) is a way for computers to translate text. It uses math models to change text from one language to another. SMT looks at a lot of bilingual text. It learns how words and phrases in one language match those in another language.

SMT typically consists of three main components:

Translation model: This component uses statistical models to determine how words and phrases in one language correspond to words and phrases in another language. The translation model is trained on a large corpus of bilingual texts, which allows it to learn the statistical patterns of language use.
Language model: This component generates the target language text by predicting the most likely sequence of words based on the source language input. The language model is trained on monolingual text in the target language, allowing it to learn the probability of different word sequences in that language.
Decoding algorithm: This component selects the best translation output from a set of possible translations generated by the translation and language models.

SMT has several advantages over other machine translation approaches, such as rule-based machine translation. SMT does not require expert knowledge in linguistics, and it can adapt to new domains and language pairs with minimal human intervention. SMT is also able to handle a wide range of text types and genres, from technical manuals to literary works.

However, SMT has some limitations. It can struggle with translating idiomatic expressions, metaphors, and other nuances of language. It also requires large amounts of bilingual data to train the models, which can be difficult to obtain for less commonly spoken languages or specialized domains.

In recent years, SMT has mostly been replaced by neural machine translation (NMT). NMT uses deep learning to make translations better. SMT is still an important method for machine translation.

This is especially true for languages with few resources. It is also useful in specific fields where there is not much training data.

Adaptive Translation™: How MotionPoint Uses AI for Website Translation

MotionPoint’s new Adaptive Translation™ model combines translation memory, algorithmic translation, and artificial intelligence to deliver human-quality translation at a fraction of the cost. Our AI translation strategy involves using Neural Machine Translation to optimise outcomes.

Neural Machine Translation (NMT) is an advanced method that uses deep neural networks to translate text between different languages. NMT is different from Statistical Machine Translation (SMT). NMT uses neural networks to learn how languages connect. SMT relies on statistical models instead.

During training, researchers train NMT models on large amounts of bilingual text data using a process called backpropagation. The model learns to improve a specific goal. This goal is to maximise the chances of getting the right translation from the source language input.

NMT requires large amounts of training data and computational resources, which can be a limitation for low-resource languages or smaller organisations with limited computing resources. NMT also struggles with rare or unknown words and can sometimes generate translations that are ungrammatical or semantically incorrect.

In recent years, NMT has become the dominant approach to machine translation, and it has achieved state-of-the-art performance on several benchmarks. Researchers continue to explore new architectures and techniques to improve the performance of NMT models, such as incorporating external knowledge sources or leveraging unsupervised learning methods.

Generic NMTs

Generic NMTs are basic AI translation tools, like ChatGPT, that produce basic translated sentence and word pairs. While the outputs may be mostly accurate, they are considered below standard because they are simply word-for-word and lack customisation. However, they tend to be a less expensive option.

Brand Adaptive NMTs

Brand-Adaptive NMT models are trained and customised to each customer's brand voice and preferences. It uses existing translation memory data, domain-relevant datasets, and our proprietary data processing pipeline to provide you with custom translations that better match your brand's glossary in other languages.

The Advantages and Disadvantages of AI Translation

Using AI translation boasts some pretty important benefits for companies looking to translate quickly and accurately.

Pros

Speed: One of the main advantages of using AI in translation is that it can work much faster than human translators. This means that large volumes of text can be translated quickly and efficiently, which can be useful in a variety of situations, such as translating legal documents, technical manuals, or website content.
Cost: AI translation can be more cost-effective than hiring human translators, especially for large translation projects. While there is a cost associated with training the AI system, once it is trained, it can work 24/7 without needing breaks or payment for overtime.
Consistency: AI translation can provide more consistent translations than human translators. Since AI systems follow a set of rules and algorithms, they are less likely to make errors or deviate from the intended meaning of the text.

Cons

AI in translation has some amazing benefits, but it doesn’t come without its limitations.

Quality: While AI translation has improved greatly in recent years, it still cannot match the quality of a human translator, especially when it comes to more nuanced or creative translations. This is because AI systems often struggle with context, idiomatic expressions, and other subtleties of language.
Cultural Differences: Language is not just about translating words, it's also about understanding culture, customs, and values. AI systems may not always understand these nuances, which can lead to translations that are not appropriate or accurate for the target audience.
Limited languages: Not all languages are supported by AI translation systems, and even for those that are, the quality may vary depending on the language pair. This can limit the usefulness of AI translation in certain regions or for certain languages.

Overall, AI translation has the potential to greatly improve the speed, consistency, and cost-effectiveness of your projects. However, it may not be suitable for all types of translations, and the quality may not match that of a human translator, especially for more complex or creative translations.

Learn about the differences between human and machine translation

The Future of AI Translation for Websites

AI translation helps improve website translation. However, human translation and editing are still necessary. They correct errors and make sure the content feels local and relevant to the audience.

AI cannot replace human touch, but it helps human linguists do their jobs better. It also allows translation companies to offer higher quality at a lower cost to customers.

Human translators can actually benefit from AI translation assistance by using tools that provide real-time suggestions and edits. Some AI tools are also able to offer metrics on translated texts that analyse the quality of the translation. It's clear that combining the benefits of both human and machine translation will lead us to the best outcome possible.

Learn how you can leverage AI translation tools by partnering with MotionPoint