What is AI Translation?
Learn about the future of website translation in light of AI and other machine learning tools.
Learn about the future of website translation in light of AI and other machine learning tools.
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.
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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.
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 Übersetzung Ihrer 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:
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
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:
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 Neuronale Maschinenübersetzung (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.
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 optimize 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 maximize 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 organizations 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.
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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 customization. However, they tend to be a less expensive option.
Brand-Adaptive NMT models are trained and customized 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.
Using AI translation boasts some pretty important benefits for companies looking to translate quickly and accurately.
AI in translation has some amazing benefits, but it doesn’t come without its limitations.
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
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 analyze 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
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