![]() ![]() Anything you want to keep must save to permanent storage, like a hard drive or solid-state drive. This is much slower than actual RAM, which is why you notice slowdowns when Windows has to use it.įREE CHEAT SHEET: The Ultimate List of Helpful Windows Alt Codesīecause RAM is volatile, you'll lose its contents when your computer shuts off. When your computer runs low on RAM, it uses a part of the storage drive called the page file, which acts as pretend RAM. The more RAM that's in your machine, the more programs you can run at once without negatively affecting performance. It's a short-term storage medium that holds programs and processes currently running on your computer. See our full explanation of RAM for more details. And linguists can enjoy a more streamlined process – no more wasted time on reviewing context matches and editing fuzzy matches, because automation quickly and accurately identifies the areas requiring linguistic review.Before we dive into tips on how to clear RAM on Windows, let's briefly describe what RAM does in case you're not familiar. Clients can count on reduced costs as context matches and 100% matches will no longer need to be manually reviewed. We expect to improve linguistic quality in all projects that use the AI-cleaned TM. The goals of automated TM cleaning are multiple. We issue a final, easy-to-understand report comparing before and after cleaning, detailing the number of errors fixed and TM distribution. The removal of duplicate TM segments is followed by consistency checks and a final spot-check. The automated TM cleaning is examined by Argos linguists. The quote is based on the total number of issues. We use our AI-driven system to process the TMs and generate a TM distribution report. The resulting QA report for auxiliary services and AI services shows the overall health and weaknesses of the TMs. We help our clients define the scope of content for review and auxiliary services. Regular expressions: Are there differences in units of measurement, spelled out numbers, or symbols?Īrgos carries out the process over four phases.Glossary: Does it adhere to terminology? (For large TMs, we recommend 100 or fewer terms.).Numbers: Are there numerical differences between source and text?.Consistency: Is one text source translated in multiple ways? (This excludes inconsistencies that are intentional or context dependent.).These are augmented by other TM cleaning checks: The Layer 2 AI is trained to analyze the target and source to determine if a segment should be translated or not. Layer 1 addresses TM quality distribution by categorizing the TM segments. Our multiple AI networks work in harmony. We can now use AI to automate TM cleaning – restoring data quality, consistency, and cost efficiencies to the localization process.Īrgos AI engineers have developed a process that works with:Īll at a fraction of the cost and time needed for manual review. very old (and often obsolete) entries in TMs.inconsistencies between corporate terminology and the TM terms.multiple translations for the same source segment.reused 100% matches and context matches without review, introducing TM errors.Sidestepping TM cleaning often results in: Which is why it was done rarely (if ever). It was even more difficult when using multiple vendors. In the past, cleaning TMs has been a long, tedious, and manual process. Improving linguistic assets – by cleaning translation memory data – can mean consistent results, lower production costs, and faster time-to-market results. And project outcomes suffer.Īrgos is committed to delivering high-quality translation content that brings value to your products and services. Without these, their high value gradually decreases. They’ve improved content quality and project consistency.īut TMs age over time. They’ve stored billions of words and helped saved millions in costs. Translation memories (TMs) have been the unsung heroes of the localization industry for almost 30 years. The cleaned data boosts the wins of machine learning (ML) in localization – namely consistent high quality, lower costs, and faster time-to-market results across projects, products, and services. With our new AI-driven offering, Argos brings automation speed to translation memory data cleaning. ![]() The challenge, however, is to ensure data quality in project after project without sacrificing time – and cost – efficiency gains. Leveraging the power of your translation memory (TM) in new projects requires a clean dataset. ![]()
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