Samuel Läubli, Partner and CTO at TextShuttle, joins SlatorPod to talk about the ins and outs of a language technology provider, the current state of machine translation, and his experience as a researcher and an entrepreneur.
The CTO touches on his background in Computational Linguistics and decision to go back to the academe in 2016 to learn more about the then-emerging neural models for machine translation. He gives his take on the current state of machine translation, particularly weaknesses around sentence-by-sentence structure and limited control.
Samuel discusses his thesis, which tackles three key challenges in MT for professionals: quality, presentation, and adaptability. The conversation turns philosophical as Samuel debates whether machine translation can become truly creative without artificial general intelligence — or if it will always be considered imitation.
He then walks listeners through TextShuttle’s business model as well as the key problems the company solves for clients, ranging from producing MT systems to helping with configurations, workflows, and training translators.
Simon also shares his insights on the future of MT, unpredictable as it may be, and TextShuttle’s initiatives with controllability and the adaptive machine translation paradigm.
First up, Florian and Esther discuss the language industry news of the week, in a tech-centered episode.
This week, RSI platform Interactio announced that it had raised USD 30m in series A funding, led by VCs Eight Roads Ventures and Storm Ventures.
Esther delves into Straker’s 100-page annual report, which showed the Australia-listed LSP’s 13% revenue growth to USD 22.6m for the 12 months to March 31, 2021. Straker shares jumped more than 14% the day results were announced.
The duo also discusses Akorbi, another fast-growing language service provider (LSP), which recently acquired the low-code process automation platform RunMyProcess from Fujitsu — a surprising move by the company as they expand to business software unrelated to translation.
Heading to Japan, Florian goes over Honyaku Center’s 2020 financial results, which saw revenues decline 14% to USD 91m and operating income nearly halved to USD 3.8m.
Florian closes the Pod full circle with more machine translation news: a research paper presented by Bering Lab about IntelliCAT, an MT post-editing and interactive translation model; and, out of big tech, Microsoft Document Translation, a recent addition to their enterprise MT offerings.
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