How do you evaluate and mitigate the environmental impact of training large ML models?

Instruction: Discuss approaches for assessing and reducing the carbon footprint associated with the computational demands of training large ML models.

Context: This question assesses the candidate's awareness and strategies for addressing the environmental impact of the resource-intensive process of training large ML models.

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The way I'd approach it in an interview is this: I evaluate environmental impact through training duration, hardware efficiency, energy source, rerun frequency, and whether the business value justifies the compute footprint. Mitigation starts with avoiding unnecessary training and reusing...

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