Quality estimation › FAQ › Who invented quality estimation?
Machine translation quality estimation first evolved as a research task in the early 2010s with the support of professor Lucia Specia and industry folks like Radu Soricut at Google, before the era of deep learning. Professor Specia and her team released multiple open-source machine learning libraries and frameworks, and a book on the topic.
Unbabel, a startup backed by Y Combinator, the top accelerator, built new type of translation company around quality estimation models and manual human translation, and it open-sourced libraries and shared research.
ModelFront launched the first quality estimation API and created the category in the 2020s, based on LLMs that supported more than 100 languages.
ModelFront soon made AI to check and fix AI work in the real world, for Fortune 500 translation buyers, by taking responsibility for keeping human quality, right inside legacy systems.
While translation is the first generative task, the basic idea is not new, nor unique to translation. Automatically triggering human intervention is key to autopilots and now self-driving cars. And among other language generation tasks, there are now startups like Momentic — AI verification for coding.
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