Curating datasets, reviewing user-generated content, and liaising with locals — all in a day’s work for a linguist hired by big tech. (No computer science degree or published research required.)
SlatorCon tour took in four global cities across three continents in 2018 and featured a grand total of 35 speakers representing the full breadth of the language industry from startups, language technology and language service providers to the buy side, finance and academia.
After an extraordinary year, our look back on 2021 — from Big Tech to big buys, machine translation to translators’ job prospects — shows the language industry is thriving.
How not to fall prey to bogus LSPs, arrests for pirated translations, translation missteps seen around the world, humble admissions from online giants, and the end to the ownership battle for the largest language service providers — these were the hottest stories of 2018.
Hot take on SlatorCon San Francisco 2018. A rundown of main themes and speakers from Slator’s one-day flagship event for the language industry including photo gallery.
The Tencent Machine Translation is now available as a fully-managed engine within Memsource Translate
US and Chinese tech giants continue to churn out research on speech-to-text translation, machine translation for rare languages, and more. Time to check in.
In this fifth monthly edition of our buyer tracker, we provide SlatorPro subscribers an easy-to-use selection of some of the most important changes happening among buy-side decision-makers.
Backed by big China tech, language data startup UTH International raised a Series C, bringing total funds raised to about USD 30m.
Slator’s inaugural comprehensive language industry market report. It examines total market size, the 10 main end-buyer industries, competitive landscape, productivity tech, NMT and much more.
Asian languages present unique challenges for NMT researchers, and a key to unlock emerging economies for providers. How far along is NMT for Asian languages?
Long the domain of academia, fundamental research in machine translation has become a battleground for big tech and niche providers.
Through five case studies and nearly 30 commentaries from the buy (enterprise, government, and more)- and sell-side (LSPs), this report shines a light on the sentiment of industry practitioners towards current-state NMT technology.
Executives from Wordbee, GoPro, and Tencent discussed a number of key issues at SlatorCon San Francisco 2018 during the Technology Panel, and one takeaway was the limitations of neural machine translation.
Research submissions on neural machine translations ballooned from 91 in the first half of 2017 to 196 in the first half of 2018, although by July 2018 submissions were slowing down.
TransPerfect buys San Francisco-based TranslateNow in first acquisition since legal battle ended. Sales up 21% to USD 275m in first five months of 2018 as execs who had left in protest over Lionbridge bid begin to return.
Some familiar names helped pushed May 2018 to the top of the charts in terms of neural machine translation research. Meanwhile, the hottest research trends appear to be the race to better quality and translating low-resource, non-Latin languages.
Tencent’s attempt to showcase their latest AI voice recognition and real-time translation engines backfired. Netizens screenshot and circulated embarrassing mistakes, sparking off an online debate on when and what jobs will be replaced by AI.
As interest in neural machine translation reaches new heights — with even Mark Zuckerberg posting about it on his personal Facebook page — academia continues to churn out NMT papers at a record clip; 2017 output already on par with whole of 2016.
Machine translation companies watch out: Baidu President Zhang Yaqin says supercomputing capabilities like machine translation make them competitive, steps up deal-making.
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