Episode Link
https://share.snipd.com/episode/b1e87f81-98bf-4111-9206-990ae9bebb8f
Episode publish date
August 12, 2025 5:00 PM (UTC)
Last edit date
Aug 27, 2025 1:07 AM
Last snip date
August 27, 2025 2:02 AM (GMT+1)
Last sync date
August 27, 2025 2:03 AM (GMT+1)
Show
MLOps.community
Show notes link
https://podcasters.spotify.com/pod/show/mlops/episodes/LinkedIn-Recommender-System-Predictive-ML-vs-LLMs-e36n94c
Snips
11
Warning
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Your snips
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[00:07] LLMs Reduce Feature Engineering Burden
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[07:09] Mitigate LLM Latency With Distillation Or Offline Use
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[09:16] Eval Criteria Stay The Same
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[11:58] Prompts Replace Much Of Feature Design
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[15:30] Compare LLMs Directly Before Replacing Models
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[18:29] LLMs Simplify Multi-Model Pipelines
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[24:21] Use LLMs For Planning; ML For Final Ranking
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[27:09] LLMs Ease Cold-Start Problems
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[31:49] Smaller Models Can Beat LLMs For Narrow Tasks
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[34:58] Be Cautious With Agentic AI In Production
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