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What will language AI look like in 2022?

The IT industry is booming. Research from McKinsey suggests that we saw five years’ worth of digital adoption in just eight weeks at the start of the pandemic. As the industry develops, so does the technology we use every day, including artificial intelligence. So, what will AI look like in the industry in 2022?

What do we mean by artificial intelligence?

The term AI is becoming so widely used that we don’t always stop to think what it really means. As a recent Forbes article explains, artificial intelligence should be just that: intelligent. AI needs to learn, change, and rewrite itself in response to new information.

AI can now be found in a wide range of industries, from automotive to translation and beyond. Sci-fi films would have us believe that this means we’re approaching the point of human obsolescence, but researchers at MIT suggest otherwise.

They explain that “recent fears about AI leading to mass unemployment are unlikely to be realized”. Instead, they believe AI will enable new industries to emerge, creating more new jobs than those that are lost to AI.

Artificial Intelligence in 2022 and beyond: language AI

AI is already becoming more commonplace in language services, and this looks set to continue in the next few years. As machine translations improve, some of the work can be simply post-edited by human translators. In fact, Gartner predicts that, by 2025, 75% of translation work will move in this direction. So, what other advances can we expect to see?

Metadata-driven machine translation

If you search for a definition of metadata, you’ll probably come across explanations that say it’s “data about data”. What this really means is metadata gives us extra information about our data. It describes the data in some way.

When it comes to translation, this might be aspects such as the age, gender, and background of the writer, or the register and domain of the text. These aspects can all inform the way a text is formed and therefore its translation.

Metadata-aware machine translation would be highly trained, intelligent, and responsive to these types of factors, helping create reliable and accurate translations through language AI.

Neural networks and deep learning

Some language AI software uses technology modelled on the human brain. These artificial neural networks allow the AI to learn and make advanced predictions about which word should be used in a translation. As IBM explains, “a neural network that consists of more than three layers” can be considered deep learning.

Artificial Intelligence in other industries in 2022

Gartner recently identified twelve key technology trends for 2022. One AI-based trend they listed was generative AI which learns about artifacts and generates innovative new creations that are “similar to the original but doesn’t repeat it”. This could lead to advancements in everything from creative video content to medicine R&D.

Whatever 2022 holds, it’s always best to work with industry experts who can add value to your project. At Future Group, we have over 25 years’ experience in translation and other language services. We work with businesses around the world to help them expand into MENA countries.

To find out more, please get in touch.


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