This article explains the concepts of batches and epochs in the context of training machine learning models, using a hypothetical startup called "Phish & Chips" that aims to detect fraudulent emails. It details two approaches for feeding data to a model: processing the entire dataset at once, which is infeasible due to GPU memory limitations, and processing one email at a time, which is inefficient and provides a noisy learning signal. The piece sets the stage for discussing more scalable data feeding methods. AI
IMPACT Clarifies core concepts for those building or understanding AI systems.
RANK_REASON The article explains fundamental concepts of ML training infrastructure rather than announcing a new development.
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