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#190 Where the ‘Translator Still Feels Like a Translator’ with Bureau Works’ Gabriel Fairman
Manage episode 383060652 series 2975363
Gabriel Fairman, Founder and CEO of Bureau Works, joins SlatorPod to talk about the potential of generative AI in translation management.
Gabriel shares the origin story of Bureau Works, where over the years his perspective shifted towards viewing translation as an information management challenge, leading Bureau Works to transition into a tech-enabled business.
Gabriel discusses the challenges and opportunities presented by large language models, touching on issues of cost, workflow integration, and the potential for a more interactive and fluid translator-computer relationship.
Gabriel rejects the idea of comparing language models like GPT to human translators, viewing them as aids to improve the human experience rather than alternatives.
Gabriel Fairman explains the flexibility of Bureau Works' UI, which aims to optimize productivity and a sense of authorship, in contrast to the repetitive and frustrating nature of traditional machine translation post-editing.
BWX is concentrating on simplification in 2024, introducing features like the learning terms tool, and aiming to integrate translation seamlessly into various tools and simplify project creation and management.
Розділи
1. Intro (00:00:00)
2. Overview of Bureau Works (00:00:52)
3. Bureau Works' Origin Story (00:03:21)
4. Service Offering (00:07:07)
5. Impact of Large Language Models (00:08:49)
6. Winning the Innovation Challenge at LocWorld (00:11:38)
7. Bureau Works' User Interface (00:13:28)
8. Linguists' View of AI (00:17:41)
9. Old Paradigm Versus New Paradigm (00:19:54)
10. Cost of LLMs (00:22:52)
11. Why is Translation so Hard? (00:27:31)
12. Building the Tech Stack (00:32:01)
13. Competitive Pressure (00:35:18)
14. Where the Role of the Linguist is Going (00:37:43)
15. How Translation at University is Changing (00:41:58)
16. Machine Translation Quality Estimation (00:45:11)
17. Competing with Well-Funded Companies (00:47:49)
18. Roadmap Going Into 2024 (00:51:59)
213 епізодів
Manage episode 383060652 series 2975363
Gabriel Fairman, Founder and CEO of Bureau Works, joins SlatorPod to talk about the potential of generative AI in translation management.
Gabriel shares the origin story of Bureau Works, where over the years his perspective shifted towards viewing translation as an information management challenge, leading Bureau Works to transition into a tech-enabled business.
Gabriel discusses the challenges and opportunities presented by large language models, touching on issues of cost, workflow integration, and the potential for a more interactive and fluid translator-computer relationship.
Gabriel rejects the idea of comparing language models like GPT to human translators, viewing them as aids to improve the human experience rather than alternatives.
Gabriel Fairman explains the flexibility of Bureau Works' UI, which aims to optimize productivity and a sense of authorship, in contrast to the repetitive and frustrating nature of traditional machine translation post-editing.
BWX is concentrating on simplification in 2024, introducing features like the learning terms tool, and aiming to integrate translation seamlessly into various tools and simplify project creation and management.
Розділи
1. Intro (00:00:00)
2. Overview of Bureau Works (00:00:52)
3. Bureau Works' Origin Story (00:03:21)
4. Service Offering (00:07:07)
5. Impact of Large Language Models (00:08:49)
6. Winning the Innovation Challenge at LocWorld (00:11:38)
7. Bureau Works' User Interface (00:13:28)
8. Linguists' View of AI (00:17:41)
9. Old Paradigm Versus New Paradigm (00:19:54)
10. Cost of LLMs (00:22:52)
11. Why is Translation so Hard? (00:27:31)
12. Building the Tech Stack (00:32:01)
13. Competitive Pressure (00:35:18)
14. Where the Role of the Linguist is Going (00:37:43)
15. How Translation at University is Changing (00:41:58)
16. Machine Translation Quality Estimation (00:45:11)
17. Competing with Well-Funded Companies (00:47:49)
18. Roadmap Going Into 2024 (00:51:59)
213 епізодів
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