Category: Technology
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Use of AI to create designs that adapt to your global markets (part I)
In my last post I explored how to obtain international content to create designs that adapt to global markets. I explained how the traditional method, pseudolocalization, is fast but imprecise, since it always assumes a worst-case expansion that may not reflect reality. I suggested a more modern approach: using an AI prompt to identify the…
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How to start your product’s global journey
With the rise of large language models (LLMs) and their so well known translation capabilities, one big question keeps popping up: Do you still need a computer assisted translation (CAT) tool to take your product global?
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SMS for your global audience
One of the most overlooked areas in global communication is the technical limitations of reaching a worldwide audience, and SMS is one of the least understood.
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Using LLMs to review source content before translation
One of the biggest challenges in localization is dealing with ambiguous or incorrect source content. Because of the automation pipelines many companies use, content is often sent for translation the moment it’s detected – whether it’s ready or not.
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Automating translations using Json scripts
One of the biggest advantages of Large Language Models (LLMs) is their ability to translate content while considering its context. Today, I’m sharing how to automate the translation process using OpenAI and a simple JSON script.
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When to start a proper globalization strategy
Today, let’s look at when a company should start building a globalization strategy. It may seem easy to say,”’we’ll deal with it when we get there,” but waiting too long can limit both impact and profitability if global expansion becomes a goal down the line.
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LQA importance + issue categorization
In a previous post, we discussed LQA testing and the different approaches teams can take to cover it. However, we didn’t touch upon its importance or the categorization of issues. Let’s talk about it!
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Visual testing – a new approach to LQA?
In today’s post, I want to focus on one of the most expensive areas of the localization process that ensures the quality delivered to our end users: linguistic quality assurance (LQA).
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Use of metadata in conjunction with LLMs to improve MT output
During our time off this summer, I’ve been diving into upcoming trends in the LLM (Large Language Models) space and how they’re gradually approaching MT (Machine Translation) quality. However, one aspect that surprises me is the lack of discussion around using metadata in translation resources to enhance MT/LLM output.
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Boosting efficiency: early localization after design phase
Starting the localization phase after code implementation usually leads to time and quality issues.