American theoretical physicist Richard P. Feynman once stated that: “[The human race’s] responsibility is to do what we can, learn what we can, improve the solutions, and pass them on.” While this may seem like a very broad statement to begin with, it speaks at the very heart of today’s word and what it means to all of us in our daily lives. After all, as humans and simply in our daily activities, we are never really satisfied with maintaining the status quo: we want things to be better, we want improvement. Still, we realize that improvement requires doing something different. For example, using a metaphor from exercising, if you want to increase your upper-body strength, simply doing more cardio isn’t the answer – we need to add something special or specific, which is the basis for today’s word.
Interestingly, though both our term, augmenting, as well as its English root word, augment, have the same heritage – from the Late Latin augmentare, meaning ‘to increase’, via the Old French augmenter – they also were both introduced in the same work, Lanfranc of Milan’s Science of Cirgurie, which was translated into English circa 1400. The word augment, meaning ‘to make greater, add to, or supplement’, is first mentioned, writing that: “It is necessary for to augment nourishing of the body with good wisdom.” Following this, we see the word augmenting, which is the gerund form of augment, defining it as ‘the action of making something greater, supplementing or adding to it’, appearing as “For nourishing & augmenting of the limes.” in the text itself.
In many ways, augmenting something is a reminder of the old BASF advertising campaign that stated: “At BASF, we don’t make a lot of the products you buy, we make a lot of the products you buy better.” Drawing a parallel to the translation industry, many see human translation and machine-based translation as two separate, monolithic entities, where consumers are forced to either choose one or the other; however, this black-or-white point of view ignores the fact that human and machine-based translation can perfectly augment each other. While it is true that machines can more efficiently process the bulk of translation work due to their speed, their lack of cultural understanding and inability to recognize style, tone, and context plays into the hand of what makes human translation so work-specifically precise and meticulous. Used separately, both forms of translation have their drawbacks; however, by augmenting one with the other, you can achieve a sum that is greater than either of its parts, which is ultimately a benefit for clients.
At EVS Translations, the augmented translation model best combines scalable neural machine solutions with in-house human translation talent to close the translation gap for global companies.