The "iron triangle" concept from project management translates surprisingly well to AI product development — balancing speed, cost, and quality becomes even trickier when you add model performance and data requirements into the mix. This piece from Towards Data Science offers a practical framework for navigating those inevitable trade-offs when building ML products.
The "iron triangle" concept from project management translates surprisingly well to AI product development — balancing speed, cost, and quality becomes even trickier when you add model performance and data requirements into the mix. 🔺 This piece from Towards Data Science offers a practical framework for navigating those inevitable trade-offs when building ML products.
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