A blindfolded person on a mountain
Imagine standing on a mountainous terrain, completely blindfolded. Your goal: reach the lowest point in the valley. You can’t see anything, but you can feel the slope of the ground beneath your feet. What do you do? You move in the direction where the ground goes down, one step at a time. If it slopes more steeply to the left, you go left. If it drops more to the right, you go right. With each step, you feel the slope again and redirect yourself.
This strategy, so simple and natural, is exactly what neural networks use to learn. Every time an AI model improves — learning to recognize a face, translate a sentence, or generate text — it does so by descending through a mathematical landscape, one step at a time, following the slope.
It’s called gradient descent, and it’s arguably the most important algorithm in modern machine learning.
