Florian and Esther discuss the language industry news of the week, kicking off with a sneak peek into the brand new Slator 2022 Language Industry M&A and Funding Report. Spanning 44 pages, the report covers 62 M&A transactions and 18 startup and tech funding rounds.

Following the latest research in ChatGPT, Intento published an article comparing ChatGPT translations to translations done by other stock MT engines. Florian discusses the results with ChatGPT performing well for English to Spanish but found lacking for English to German.

The Committee for Organizing the Olympic and Paralympic Games is looking for an interpreting technology provider who can offer a platform for remote simultaneous interpreting (RSI). The winning candidate will supply an RSI platform for more than 60 interpreters working in 11 languages before and during the Games.

Esther shares her experience watching Netflix’s 1899, which brought together nine source languages, and a number of translated versions: 14 dubbed languages and 32 subtitle options. The one-season series was distributed in 58 countries and was made up of an international cast and crew.

Over in Ireland and London, Keywords Studios are seeing a healthy demand for game localization after posting 22% organic growth in the second half of 2022. The gaming services giant expects full-year revenue and profits to slightly exceed previous guidance.

Tanya Bogin, Managing Director of Craft London, joins SlatorPod to talk about the company’s end-to-end creative production services across all media channels and languages.

Tanya discusses her route into the language industry; from working as a radio station manager to entering the transcreation industry with Craft. She talks about how the company brings creative ideas to life through cultural adaptation, translation, and transcreation.

Tanya outlines the rigorous testing process behind recruiting transcreation specialists and how their bespoke workflow yields successful results with clients. She touches on the role of language technology at Craft with a combination of best-of-breed cloud-based CAT tools and human-driven translation.

Tanya talks about the impact of AI and how they have implemented features like SEO, dynamic content optimization, and virtual production to improve workflow. She shares how they partnered with AI video generation platform Synthesia to transcreate JustEat’s Snoop Dogg advertisement for the global market.

The pod rounds off with Craft’s initiatives for 2023, including continuing to pay translators fairly and using AI to increase the sustainability of their productions.

In this week’s SlatorPod, LXT Chief Growth Officer Phil Hall joins us to talk about the company’s journey, from providing high-quality Arabic data for a Big Tech company to expanding into 750 languages.

Phil shares his background teaching linguistics and leading business development for Appen before joining LXT. He discusses the key findings from The Path to AI Majority report, from the maturity levels among 200 executives surveyed to which industries are trailblazers in AI adoption.

Phil touches on search relevance ranking as a method to retrain machine learning and give more relevant results. He gives his thoughts on ChatGPT and why he considers it a step change in AI.

Phil talks about LXT’s growth strategy, with M&A a potential avenue to acquire new customers and improve the technology stack. He goes over some of the legal and security considerations when it comes to data, with permission and secure facilities taking priority.

The pod rounds off with Phil’s take on where the AI industry is heading, with quite a long way to go before it becomes stable, low risk, and deployed with absolute confidence.

Google’s Head of Product, Translation AI, Mallika Iyer, joins SlatorPod to talk all about the company’s new Translation Hub. 

Mallika begins with her journey from software engineer to leading all of the translation products for Google Cloud, most recently Translation Hub. She shares the motivation behind launching the hub, where they saw that overall demand for translation had increased, but budgets necessarily hadn’t.

Mallika discusses the basic and advanced tiers the hub offers, with the latter including domain-specific translation, translation memory, and translation quality prediction. She explains how the hub has gained traction early on with languages of lesser diffusion in addition to the major FIGS or CCJK combinations.

Mallika talks about a case study with Avery Dennison and how they rolled out Translation Hub to all their employees to improve language communication and promote an inclusive workplace culture. She expands on the different sectors the hub serves, from those with limited budgets in the public sector to those on the opposite side in retail and manufacturing. 

The pod rounds off with Mallika laying out the Hub’s roadmap for 2023, with plans to add more document types, improve user experience, and integrate with third-party products. Translation Hub’s ultimate goal is to make the hub more accessible with new features while keeping its simplicity.

Florian and Esther discuss the language industry news of the week, with the hype surrounding ChatGPT. Slator joined in by prompting ChatGPT to answer questions as if it were a translation manager.

After reports back in November 2022 stated that DeepL was in the final stretch of closing a major investment round, DeepL has finally confirmed that it raised funds from VCs at a billion-dollar valuation.

Translator Scammers Directory shared their annual report of scammer activities in 2022. Last year saw the first dip in new scammer IDs since 2018, signaling lower payoffs for imposters involved in the CV scam.

Florian and Esther then talk about the best and worst-performing listed language service providers (LSPs) in 2022. Out of the 12 LSPs, only Zoo Digital and Honyaku Centre delivered a positive performance, while Appen’s stock continued to plunge.

A large Amazon study titled “Large Scale Study of Human Localization With Insights for Automatic Dubbing” reviewed hundreds of hours of Prime Video content. The researchers found that human dubbers prioritize translation quality and speech naturalness over timing and lip sync.

Slator waved goodbye to the Language Industry Job Index after four years as a result of changes to the availability of the underlying data.

In this week’s SlatorPod, Happy Scribe CEO André Bastié joins us to talk about building a unified platform for transcription and subtitling.

André discusses the journey to co-founding Happy Scribe during his studies where he accidentally came across the challenge of transcription and built a first prototype with his flatmate and now CTO, Marc Assens Reina.

The CEO shares how their product development has evolved, from initially deploying the Google Speech API to connecting to various off-the-shelf systems to, now, building their own custom models. He talks about how being a bootstrapped company forces them to focus on producing results with limited resources.

André touches on the different customized features that allow users to create a vocabulary list, build their own dictionary, and adjust the number of characters per line for subtitling projects.

He gives his take on what’s driving the popularity of subtitles in short-form content and how subtitling differs between TikTok and long-form entertainment.

The CEO talks about the positives and negatives of Whisper, OpenAI’s open-source ASR model, and its impact on the AI space. The pod rounds off with Happy Scribe’s roadmap for 2023, including some interesting changes to pricing.

In the final SlatorPod episode of 2022, we are joined by Marco Trombetti, cofounder and CEO of Italy-based LSP Translated. Marco joins us two years on from our episode with Translated’s other cofounder, Isabelle Andrieu.

Marco breaks down the LSP’s Singularity in AI research project and defines what singularity means in translation. He walks us through the process and the vast data collection effort behind the research, with “time to edit” emerging as the key performance indicator for machine translation quality.

He talks about whether Translated has reached a plateau of productivity in postediting and the challenges of building a user interface for interacting with natural language. He also gives his take on the importance of owning an adaptive solution for machine translation like ModernMT.

Marco shares Translated’s approach to working with some of the world’s biggest companies such as Airbnb. He explains how they see financing as a requirement to reach their goals — which eventually fuelled their decision to secure USD 25m in growth equity.

The CEO shares his thoughts on ChatGPT. He thinks big language models will be the future of search and natural language will become the primary way of interacting.

Initiatives such as participating in the Ocean Globe Race 2023, the Imminent research center, and Pi Campus are all central to spreading their values and creating an innovative community, Marco concludes.

In this week’s SlatorPod, we are joined by Mark Lawyer, General Manager of Trados, the key technology product line of UK-based Super Agency RWS.

Trados is a translation technology adopted by hundreds of thousands of freelance translators, LSPs, and enterprise customers — the three main market segments of the localization supply chain.

Mark begins with his journey to joining the localization industry straight out of university, with roles spanning business development, solution architecture, and global customer experience management. He shares some of Trados’ milestones starting with its creation in 1984.

Mark talks about the flexibility of the Trados platform and why they offer cloud capabilities with the desktop app to provide a hybrid working environment for translators. He discusses how user feedback allows them to release hundreds of best-in-class features each year.

Mark highlights how user experience and accessibility are critical to Trados, where there are multiple configurations available to users based on their role. For example, a post-editor will have the Track Changes feature and fuzzy-match repair available to them. With more than 270,000 linguists using the platform, Mark shares how they strike the right balance between functionality and features without overwhelming those users.

Mark shares his views on Google’s Translation Hub and how it can bring awareness to the industry, which he sees as still being very fragmented. The pod rounds off with Trados’ roadmap for 2023, plans to invest money in security, AI-driven features, the modern user experience, continuous localization, and building out that ecosystem.

DeepL launches then pulls new AI-based writing tool, translator and interpreter employment declines in Germany, job index dips for fourth time in 2022, Blu Digital Group expands further into media localization, and Deluxe buys Post Haste Digital.

Joining SlatorPod this week is Ev Fedorenko, Associate Professor of Neuroscience at the Department of Brain and Cognitive Sciences, MIT. Ev also runs EvLab, an MIT language lab that discovers how the human brain creates language.

Ev talks about the different hypotheses concerning the origin of language and how it has likely been a gradual evolution. She shares a number of intriguing research findings on the relationship between language and abstract representations of structure (i.e., complex thought).

Ev discusses how language processing takes place and how we can use brain imaging to compare language with other non-linguistic tasks, such as solving math problems and composing music. She questions whether specific languages can be objectively easy or difficult to learn as an adult.

She also considers what sets polyglots apart when it comes to learning languages and some of the generalizations made in research. Ev talks about how language processing in machines like GPT-3 compares to that in humans. She argues that it would be more fruitful to build language systems that are structured similar to the human brain.

Ev concludes with the collaboration between academia and the booming field of applied AI, despite different goals. She touches on the MIT Quest for Intelligence, which brings together scientists and engineers to build better human-like models for the benefit of society.