SlatorPod

#73 What’s New in Machine Translation with TextShuttle CTO Samuel Läubli

May 28, 2021 Slator
SlatorPod
#73 What’s New in Machine Translation with TextShuttle CTO Samuel Läubli
Show Notes Chapter Markers

Samuel Läubli, Partner and CTO at TextShuttle, joins the pod to talk about the ins and outs of a language technology provider, and the current state of machine translation.

The CTO touches on his background in Computational Linguistics and decision to go back to the academe in 2016. 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. He 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.

First up, Florian and Esther discuss the language industry news of the week, where 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. 

The duo also discusses Akorbi, another fast-growing language service provider (LSP), which recently acquired the low-code process automation platform RunMyProcess from Fujitsu.

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.

Agenda and Intro
Interactio closes USD 30m series A
Straker's annual report
Akorbi Digital acquires Fujitsu RunMyProcess
Honyaku Centre financial results
Research from Bering Lab
Microsoft document translation
Samuel Läubli joins the pod
Samuel’s personal background
TextShuttle in a nutshell
How good is machine translation?
Document level content
Thesis on “Machine Translation for Professional Translators”
Top-to-bottom vs. Left-to-right arrangement
Truly creative machine translation
Textshuttle’s business model
Key problems Textshuttle is solving for clients
Sales and marketing approach
Raising capital to accelerate growth
Team structure at TextShuttle
Opinion on multipurpose language models such as GPT-3
Role of Big Tech
Machine translation outlook and key initiatives