Interview
summary
Weights & Biases builds experiment tracking tools for machine learning teams and watches hundreds of models across industries; the concrete recommendation is to save what you're doing so experiments are reproducible weeks later. The claim is that data pipelines are the single most important bottleneck for ML production, and the open questions are how many companies go cloud versus on‑prem and how often third‑party pipelines are used. Notes that functional programming / Scala skills correlate with strong engineers and hosts a panel including Richard Souter, Pete Warden and Michelle.
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