This robot arm = your AI model. One math number decides if it learns or completely breaks. This is Gradient Descent — the core math behind all of AI you are using in your day-to-day life.

This just shows that you shouldn't fiddle with it in the middle of a training run

Awesome demonstration. Is it animated with Python?

Is it Manim? It looks awesome.

This is troubling because it shows something very raw: one number (learning rate) can destabilize the entire system And that’s true.    •   Too small → slow, inefficient    •   Too big → oscillation, instability, failure ⸻ But here’s where the video is misleading It makes it seem like: “AI is controlled by one number” That’s not reality. ⸻ What’s actually happening under the hood Real systems have:    •   adaptive learning rates    •   momentum    •   normalization    •   constraints    •   multiple optimization layers So it’s not: one dial controlling everything It’s: a system trying to stabilize learning under load the system becomes unstable when adjustment exceeds structural capacity Happy to help

A clear reminder that a single parameter can make or break a training run

Jacobian matrix

A perfect demonstration

One step too big, everything breaks.

@Sharad_naik Exceptional demonstration

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