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Within translation/localization we’re all looking to ensure that the quality of the deliverable meets the expectation, in whatever way those two things are defined. Some people may believe achieving that quality is a factor that is inherent in actually doing the work, and builds around the processes. Other people may, however, think of quality as something that can be tested and evaluated after the work is done. There is a great deal of discussion about this in our industry right now. Some people, on the other hand, may not consider quality as something that should be planned, or measured in terms of...
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In a recent NPR news piece Uber Plans To Kill Surge Pricing, Though Drivers Say It Makes Job Worth It, Jeff Schneider, engineering lead at Uber describes how they are using machine learning to hack the problem of supply and demand. Initially, Uber came up with "Surge Pricing" as a feature designed to help mitigate the phenomenon of demand outstripping supply in a certain area at a certain time. Concretely, that means that when some event causes lots of people to need transportation at the same time in generally the same location, the Uber fare will automatically increase. This increase incentivizes...
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Over the last two decades our industry has spent a lot of time and energy making the localization process increasingly more efficient. Dollars spent in the process are highly leveraged thanks to the application of translation memories and machine translation, together with sophisticated expert systems and static analysis tools that help ensure that quality can still be achieved at scale. Companies that release products internationally know how to write global-ready code and content, standards exist and are generally adhered to. Companies wishing to extend into international markets for the first time have a deep bench of partners and suppliers that...
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