Our guest today is Erwin Huizenga, Machine Learning Lead at Google and expert in Applied AI and LLMOps.
In our conversation, Erwin first discusses how he got into the field and his previous experiences at SAS and IBM. We then talk about his work at Google: from the early days of cloud computing when he joined the company to his current work on Gemini. We finally dive into the world of LLMOps and share insights on how to evaluate LLMs, how to monitor their performances and how to deploy them.
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Link to Train in Data courses (use the code AISTORIES to get a 10% discount): https://www.trainindata.com/courses?affcode=1218302_5n7kraba
Erwin's LLMOps coursera course: https://www.deeplearning.ai/short-courses/llmops/
Follow Erwin on LinkedIn: https://www.linkedin.com/in/erwinhuizenga/
Follow Neil on LinkedIn: https://www.linkedin.com/in/leiserneil/
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(00:00) - Intro
(05:04) - Early Experiences
(15:51) - Joining Google
(20:20) - Early Days of Cloud Computing
(26:18) - Advantages of Cloud Infrastructure
(30:09) - Gemini and its Launch
(37:32) - Gemini vs Other LLMs
(46:15) - LLMOps
(50:50) - Evaluating and Monitoring LLMs
(57:34) - Deploying LLMs vs Traditional ML Models
(01:01:07) - Personal Stories and Career Insights
