Discover and read the best of Twitter Threads about #MachineTranslation
Most recents (6)
#Chapter9
Use Machine Translation to accelerate your translation process 🚀
A thread by @rk_process9
Use Machine Translation to accelerate your translation process 🚀
A thread by @rk_process9
Using #MT can increase the #productivity of your #translator and save time. When combined with appropriate #translation tools, it can also help improve the quality of translations for you.
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However, its important to remember that #tech is a tool that can reduce your effort, but not eliminate it entirely. For example, a car or an airplane can help you reach your destination faster, but you still need to drive or fly it.
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@rk_process9 #ChatGPT has generated more interest & debate in recent months than any other #tech in decades. It has accomplished tasks previously only seen in #scifi movies or read in fiction, marking a significant milestone in the field of #ai.
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In 1950, father of #AI - Alan Turing, devised a test where a #machine could be considered AI, if one can't differentiate its responses from a human's. If a machine can accurately #translate text from one language to another, like a human, it would pass the Turing test.
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Good morning from Brussels! We're attending #METAFORUM2022 today, bringing you updates from the world of language technology.
There are roughly 100 people in the room. And several hundred following along on YouTube: .
Join us!
Join us!
Kicking things off now is @GeorgRehm who also attended our hybrid DG TRAD Conference last year. He underlines that #multilingualism is at the heart of the European idea. 24 EU languages plus countless regional and minority ones!
Colloque Tralogy III #tralogy3
« #Traduction humaine et traitement automatique des langues : vers un nouveau consensus ? »
‘Human #translation and natural language processing: Forging a new consensus?’
2e journée
#TAL
« #Traduction humaine et traitement automatique des langues : vers un nouveau consensus ? »
‘Human #translation and natural language processing: Forging a new consensus?’
2e journée
#TAL
Technologies de la #traduction et dynamiques de pouvoir
Confining Machine Translation; Reclaiming Localization
by Alan Melby, of Brigham Young University @BYU and the International Federation of Translators @fit_ift
#machineTranslation #localization
Confining Machine Translation; Reclaiming Localization
by Alan Melby, of Brigham Young University @BYU and the International Federation of Translators @fit_ift
#machineTranslation #localization
One of the things currently on everyone's mind is obviously how the pandemic has changed the working lives of #interpreters. In my view, many of these changes are here to stay, even beyond the pandemic...
During my curation this week, I would like to discuss the Future of Interpreting, both in relation to conference and community interpreting. How has the market around you changed since you started working on it or otherwise engaging with it?
I have seen a gradual change (the rise of #ELF, #AI and #MachineTranslation among other things) over the past 12 years that has led me to develop other professional activities and interests alongside interpreting. I know many colleagues who have done the same.
The size of #NLP models have increased enormously, growing to millions, or even billions, of parameters, along with a significant increase in the financial cost and carbon emissions.
The cost associated with training large models limits the #AIresearch community's ability to innovate, because a research project often needs a lot of experimentation.
Consider training a top-performing #LanguageModel on the Billion Word benchmark. A single experiment would take 384 GPU days (6 days*64 V100 #GPUs, or as much as $36,000 using AWS on-demand instances)
