From ML Engineering to AI Engineering: A Paradigm Shift

From ML Engineering to AI Engineering: A Paradigm Shift

A Berlin startup, 2023. The team spent three months training their own classification model—curating datasets, evaluating architectures, monitoring training runs. The result: 74 percent accuracy, expensive, fragile. Then someone decided to try using GPT-4 and three targeted few-shot examples. Accuracy: 89 percent. Development time: two days. This story is currently repeating itself millions of times…

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