What is the AI training loop?

Four steps—forward pass (guess), loss (score error), backpropagation (blame weights), update (tweak)—repeated millions of times to minimize mistakes.

How does backpropagation work in AI?

Uses chain rule calculus to trace errors backward through layers, computing gradients that show each weight's fault, then adjusts accordingly.

No universal—0.001 to 0.01 common starters. Use schedulers like cosine annealing; tune via sweeps on val loss.

🤖 AI & Machine Learning

Nobody coded ChatGPT's poetry skills. It stumbled through millions of flops first. Here's the gritty training loop turning garbage weights into gold.

theAIcatchup Apr 08, 2026 3 min read

AI 'learns' via endless failure loops, not programmed smarts—pure optimization grind. 𝕏
Backpropagation pins exact weight blame with math; learning rate decides step size. 𝕏
NVIDIA and cloud giants cash in big; efficient training is the real future battleground. 𝕏

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#AI training loop #backpropagation #gradient descent #neural network training #neural networks

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Originally reported by Dev.to