Mathematics
The Gradient Descent Algorithm from a Calculus Perspective
Quick fact
Gradient descent is the backbone of training neural networks: every time a model learns from data, it's essentially performing thousands of tiny downhill steps guided by the gradient of a loss function—the calculus at the heart of artificial intelligence.
Why this is interesting
If you're on a foggy mountain and need to find the valley, your first instinct is to take a step downhill—but how do you mathematically know which way is down? That's exactly the problem gradient descent solves, using nothing but calculus.