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Shreya Shankar — Operationalizing Machine Learning
Gradient Dissent: Conversations on AI
Is There a Trade-Off Between ML and ML?
I would think that kind of over time your priorities would naturally shift. I feel like stories like that just make me like oh my god, like no one is working on ML because they're fighting their infrastructure rattles and dealing with all the tech that they introduced from having so what is the trade-off? It's hard to know where there are other stories like that or teams like that where there's a consistent regret of something that people did in the beginning that they now can't get rid of when things are in production.
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