#162 The Great ChatGPT and Translation Debate

SlatorPod

This week, SlatorPod hosts its very first panel debate with guests Adam Bittlingmayer, CEO of ModelFront, Varshul Gupta, Co-founder of Dubverse, and Mihai Vlad, General Manager of Language Weaver.
To start off, the panel participants reflect on their recent experience with ChatGPT since its launch in November 2022 and how this shapes their views on large language models (LLMs). Varshul and Adam talk about how clients view ChatGPT.
Mihai agrees with the idea that the language services industry is exceptionally well-prepared for the launch of ChatGPT due to its experience with human-machine interaction. Varshul discusses how LLMs have influenced startups like Dubverse to build prototypes that can handle edge cases.
Mihai shares the challenges of deploying LLMs in large enterprises. Adam and Varshul highlight how parameters such as security, data privacy, latency, throughput, and cost are essential to consider in an enterprise setting.
Varshul and Mihai talk about the potential of multilingual content generation from scratch and how it will affect production costs. Varshul shares how they continue to attract users throughout this AI hype and the importance of adding a UX on top of LLMs.
Adam discusses the potential for LLMs to assist translators in their work, although the implementation of this tech may take some time to become the new normal. Varshul and Mihai debate how services-focused companies should react to the rapid advancements in LLMs, whether you wait to see how things pan out or go all in to stay ahead of the curve.
The panel rounds off with emerging use cases for LLMs, from building prompt-based systems for more concise translations to addressing long-tail languages that are often overlooked by machine learning due to the fragmentation of the language industry.

Розділи

1. Intro and Agenda (00:00:00)

2. Panel Introduction (00:01:24)

3. Experience with ChatGPT (00:04:02)

4. Large Language Model Evolution (00:09:22)

5. Client Perspectives (00:12:46)

6. Language Industry Impact (00:15:57)

7. Reaction as a Startup (00:19:11)

8. Enterprise Deployment of LLMs (00:22:13)

9. Privacy and Data Security (00:26:42)

10. API Limitations (00:29:46)

11. LLM Research and Adoption (00:30:47)

12. Multilingual Content Generation (00:32:33)

13. AI Hype Impact on Dubverse (00:37:27)

14. LLMs Supporting Translators, LSPs and Enterprises (00:40:34)

15. Context and Privacy Concerns (00:47:21)

16. Open-Source LLMs (00:51:36)

17. What Should the Language Services Industry Do? (00:54:24)

18. Emerging Use Cases for LLMs (00:58:35)