Combining AI and Human Work 🤖 — with Marco Trombetti
Feb 24, 2025
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Marco Trombetti, CEO of Translated, discusses the intersection of AI and human work in the translation industry. He shares insights on the evolution of AI models, particularly the advanced translator Lara, and explores the ethical implications of AI's rapid development. Trombetti also addresses the financial costs of training AI, the potential for job displacement in translation, and the importance of regulation. He highlights how AI can enhance human productivity while urging caution on its implications for the workforce.
Regulation is essential in the AI industry to ensure fair competition and prevent monopolies from hindering innovation.
The development of Lara demonstrates a significant transformation in translation technology, combining AI capabilities with human assistance for improved accuracy.
Workers should embrace AI as a productivity tool, focusing on continuous learning to leverage its benefits rather than succumbing to job displacement fears.
Deep dives
The Role of Regulation in Market Competition
Regulation is necessary to ensure fair competition in the market, allowing all participants, especially newcomers, the same opportunities as established entities. It aims to prevent monopolies from stifling innovation and to protect against misuse of products and technologies. Instead of regulating specific tools or technologies, the focus should be on defining acceptable and unacceptable outcomes to ensure ethical practices. This approach maintains the necessary flexibility to adapt to technological advancements without stifling innovation.
Evolution of AI in the Translation Industry
The conversation highlights the historical use of artificial intelligence in the translation industry, beginning with the early days of rule-based systems that struggled to provide quality translations. With advancements in statistical machine translation and then neural networks, AI began to assist human translators effectively by enhancing speed and quality. The emergence of transformer models further revolutionized translation capabilities, leading to the development of sophisticated AI systems like Translated's latest model, which combines both AI-driven and human-assisted methodologies. This shift showcases AI's evolution from a mere tool to a collaborative partner that enhances the translator's work.
Introducing Lara: A Breakthrough in Translation Technology
Lara, the latest translation architecture developed by Translated, signifies a major advancement in the industry as it outperforms existing translation models. By merging language models with traditional translation methods, Lara enhances both accuracy and fluency while addressing common biases in translation. The system not only offers translations but also explains its reasoning and requests clarifications for ambiguities, making it a more interactive tool. This approach aims to elevate translation quality to new heights, paving the way for a near-singularity level of translation capability.
The Future Landscape of AI Models
Looking ahead, the discussion reflects on the potential plateauing of performance gains in foundational AI models due to limitations in data quality and increased costs of training. While larger models may yield diminishing returns, there remains significant room for innovation through optimization and domain-specific applications. As costs decrease and technology advances, there is hope that smaller, fine-tuned models targeting specific tasks can achieve remarkable performance. This paves the way for startups and individuals to capitalize on specialized AI solutions that solve specific industry problems more effectively than broad, general-purpose models.
Embracing AI for Everyday Professionals
For regular workers, the key to navigating the evolving landscape of AI lies in rethinking how they engage with technology. Rather than fearing job displacement, individuals should embrace AI as a tool that can enhance their productivity and effectiveness. By becoming power users of AI tools, they can gain unique insights into their respective fields, paving the way to innovative solutions or even new ventures. Emphasizing continuous learning and leveraging AI improves individual performance while also creating new opportunities and solutions in the job market.
Today's guest is Marco Trombetti!Marco is the CEO and founder of Translated, one of the largest translation companies in the world, powering translations for the likes of Airbnb, Uber, Skyscanner, and more.Translated is also an AI pioneer. It has developed its own models for more than 20 years and has recently released the most advanced translation LLM in the world.With Marco, we talked about the future of AI, combining AI and human work and the role of regulation. This is also the first interview we ever did in person. But as you will see and hear, I was recovering from a bad cough and had a bit of a low voice, hope you don't mind.(00:03:26) Introduction(00:05:45) The history of Translated(00:09:51) The use of transformers(00:12:47) Lara: the most advanced translation AI(00:17:51) The next step in AI models(00:24:01) The "Lara gap"(00:28:50) The real cost of training Lara(00:32:39) AI impact on human work in translation(00:41:16) Applying the Translated model in other fields(00:45:21) Concerns in AI applications(00:53:51) More on AI regulation(00:56:15) The state of AI startups(00:59:25) Understanding the AI game(01:03:31) AI and regular jobs—This episode is brought to you by https://workos.com—You can also find this at:- 📬 Newsletter: https://refactoring.fm- 📱 YouTube: https://youtu.be/HgKAg1rtQoE—For inquiries about sponsoring the podcast, or appearing as a guest, email: luca@refactoring.club
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