#198 Implementing Language AI in the Enterprise with Translated’s John Tinsley

SlatorPod

John Tinsley, the VP of AI Solutions at language AI agency Translated, joins SlatorPod to talk about the challenges, advancements, and future directions of AI in the language industry.
John shares his journey from founding machine translation (MT) pioneer ICONIC, selling it during the height of the pandemic to RWS, and now his current role focusing on connecting technology and capabilities with customer needs at Translated.
He touches on the challenges of managing the noise around AI and the excitement and potential of generative AI, particularly in the context of language. He discusses the impact of large language models on translation and the challenges of multilingual content generation.
John mentions the importance of having the right data for AI and highlights a new product initiative called Human-in-the-Loop. This initiative focuses on automating the process of improving MT by constantly fine-tuning it based on user feedback and human data.
He also explores the dynamic landscape of innovation in the AI field, discussing the sources of innovation, the role of big tech companies, and the challenges of keeping up with the rapidly evolving research landscape.
Looking ahead, John underscores the importance of ensuring enterprise readiness in MT, considering factors beyond just good output, such as fitting into existing workflows, cost-effectiveness, and scalability.

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1. Intro (00:00:00)

2. Professional Background and Milestones (00:01:31)

3. Return to the Language AI Space (00:03:58)

4. Role as VP of AI Solutions (00:08:46)

5. How has Machine Translation Changed? (00:10:35)

6. Massive Enterprise Adoption of Language AI (00:14:38)

7. Multilingual Large Language Models (00:19:56)

8. Translation Workflow at Translated (00:22:06)

9. Text Translation Versus Multimodal Translation (00:27:14)

10. Dubbing with matedub (00:29:34)

11. Role of Big Tech (00:35:22)

12. Keeping Up-to-Date with AI Innovations (00:38:18)

13. Roadmap for 2024 (00:43:37)