Jaroslaw Kutylowski & Rudi Bauer

Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation

What's the secret sauce behind a world-class AI translator? DeepL's founder reveals how high-quality training data became their most powerful competitive advantage.

Fireside Chat: Deep Learning, Deep Impact: Harnessing AI for Language Innovation
#1about 2 minutes

The founding story and early days of DeepL

The CEO of DeepL shares his early coding experiences and the naive mindset required to challenge established players like Google Translate.

#2about 4 minutes

How neural networks and quality data power AI translation

Neural networks learn language nuances automatically, but the quality and selection of training data remain the critical factor for high-quality translation.

#3about 4 minutes

Managing bias in translation and generative AI

Mitigating bias is a key challenge, especially for generative AI like DeepL Write, requiring careful data selection and specific technical measures.

#4about 4 minutes

The organizational challenges of scaling a tech company

Rapidly scaling a company from a few founders to over 600 employees introduces challenges in maintaining innovation speed and effective communication.

#5about 2 minutes

The future of translation and human-AI collaboration

The future of translation lies in personalization and seamless human-AI collaboration, moving beyond simple text output to real-time voice and conversational interfaces.

#6about 7 minutes

Engineering culture and product development at DeepL

DeepL fosters a tech-first culture with cross-functional teams where engineers help shape the product roadmap, balancing a strong internal vision with customer feedback.

#7about 7 minutes

Q&A on technical challenges and future integrations

The Q&A covers technical challenges like translating ambiguous pronouns, onboarding new languages via English, and handling API limits in corporate environments.

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