The Great ChatGPT and Translation Debate
Adam Bittlingmayer, Varshul Gupta, and Mihai Vlad on LLMs and machine translation, client perspectives, state-of-the-art research, and GPT’s impact on the language industry.
Adam Bittlingmayer, Varshul Gupta, and Mihai Vlad on LLMs and machine translation, client perspectives, state-of-the-art research, and GPT’s impact on the language industry.
What you need to know about machine translation quality estimation (MTQE) — from benefits and challenges to industry adoption — as discussed by Adam Bittlingmayer and Conchita Laguardia.
SlatorCon Remote September 2022 saw the biggest percentage of buy-side participants of any SlatorCon to date. Here are the highlights.
Is machine translation trained mostly on...machine translation? Research sparks discussion among MT experts. Quality issues found to be likely worse for non-English pairs, low-resource languages.
Developers praise PyTorch, Facebook’s open source framework, for its flexibility, speed, and usability. But the machine translation world is not ready to dethrone TensorFlow just yet.
New research by Google AI explores multilingual NMT on an unprecedented scale. Good for low-resource languages, less so for the rest, results show.
Language industry startups Unbabel and Lilt took to the stage at one of Europe’s largest machine learning conferences and explained how they build atop evermore sophisticated AI tech.
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