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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