The MLOps Podcast
The MLOps Podcast
Dean Pleban @ DagsHub
🛰️ Modern & Realistic MLOps with Han-chung Lee
1 hour 5 minutes Posted Mar 18, 2024 at 1:00 pm.
Intro
State of NLP and LLMs
Repeating the past in NLP
Vector databases vs. classical databases
Choosing the right LLM for an application
Advantages and disadvantages of LLMs
Where LLMs are most useful
The dark side of LLMs and can we detect it?
Thoughts on LLM leaderboard metrics
Using LLMs in regulated industries
Creating a moat in the LLM world
Evaluating LLMs
Impact of LLM on non-english languages
Thoughts on MLOps and getting ML into production
The Hardest Unsolved Problem in ML and AI
Predictions for the Future of ML and AI
Recommendations and Conclusion
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1:05:42
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Show notes
In this episode, I speak with Han-Chung Lee, a machine learning engineer with a lot of interesting takes on ML and AI. We dive into the buzz around natural language processing and the big waves in generative AI. They chat about how newcomers are racing through NLP’s history, mixing old school and new tech, and the shift towards smarter databases. Han-Chung breaks it down with his straightforward takes, making complex AI trends feel like coffee chat topics. It’s a perfect listen for anyone keen on where AI’s headed, minus the jargon.
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Timestamps:
➡️ Han Lee on Twitter – https://twitter.com/HanchungLee
➡️ Han Lee on LinkedIn – https://www.linkedin.com/in/hanchunglee/
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