Aaron Colak is the Leader of Core Machine Learning at Qualtrics, an experiment management company that takes large language models and applies them to real-world, B2B use cases.

In this episode, Aaron describes mixing classical linguistic analysis with deep learning models and how Qualtrics organized their machine learning organizations and model to leverage the best of these techniques. He also explains how advances in NLP have invited new opportunities in low-resource languages.

Show notes (transcript and links): http://wandb.me/gd-aaron-colak

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⏳ Timestamps:

00:00 Intro

00:57 Evolving from surveys to experience management

04:56 Detecting sentiment with ML

10:57 Working with large language models and rule-based systems

14:50 Zero-shot learning, NLP, and low-resource languages

20:11 Letting customers control data

25:13 Deep learning and tabular data

28:40 Hyperscalers and performance monitoring

34:54 Combining deep learning with linguistics

40:03 A sense of accomplishment

42:52 Causality and observational data in healthcare

45:09 Challenges of interdisciplinary collaboration

49:27 Outro

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Connect with Aaron and Qualtrics

📍 Aaron on LinkedIn: https://www.linkedin.com/in/aaron-r-colak-3522308/

📍 Qualtrics on Twitter: https://twitter.com/qualtrics/

📍 Careers at Qualtrics: https://www.qualtrics.com/careers/

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💬 Host: Lukas Biewald

📹 Producers: Riley Fields, Cayla Sharp, Angelica Pan, Lavanya Shukla

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