The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) Engineering Production NLP Systems at T-Mobile with Heather Nolis - #600
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Nov 21, 2022 In this conversation, Heather Nolis, a principal machine learning engineer at T-Mobile, shares her journey from neuroscience to machine learning. She discusses the challenges of deploying real-time deep learning models for customer support, focusing on supervised learning and the creation of customer intent models. Heather highlights the balance between small and large models, technical hurdles in speech recognition, and the importance of data quality. She also looks ahead to the future of NLP, exploring innovative applications in customer service and beyond.
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From Rats to AI
- Heather Nolis's neuroscience study involved keeping rats alive for a year and meticulously recording their blood pressure data.
- When told the lab's analytics team would analyze her results, she taught herself Python and bioinformatics, sparking her love for computer science.
T-Mobile's Internal Shark Tank
- T-Mobile held an internal "shark tank" where Nolis's team pitched their AI proof of concept and received $100,000.
- After successfully launching their initial model, the team secured further buy-in to develop a full-scale product.
Unsupervised Learning Falls Short
- Initial attempts with unsupervised learning revealed two major conversation topics: T-Mobile and phones, which lacked business actionability.
- This led to the decision to use supervised learning and create a custom taxonomy for real-time insights.