Why Gradients Point Up?
2026-02-04 00:00:00

As what I recall when I learned about the gradient, I was taught that the gradient represents the vector with the direction of fastest climbing. I didn’t really understand it. It is known that ∂f∂x\frac{\partial f}{\partial x} represents the rate of change for ff at xx, then shouldn’t the gradient just tell you the rate of change for each direction?

I’m using ∇f=ai+bj\nabla f = a\mathbf{i} + b\mathbf{j} for instance, but it should also apply to higher dimensions.

Proof: ∇f\nabla f is in the direction where ff increases the fastest.

Let the direction of the gradient be u=∇f∥∇f∥\mathbf{u} = \frac{\nabla f}{\|\nabla f\|}.
Say ∇f\nabla f is not the direction where ff increases the fastest. Then ∃\exists unit vector v\mathbf{v} s.t. the directional derivative along v\mathbf{v} is greater than the gradient’s magnitude

v⋅∇f>∥∇f∥\mathbf{v} \cdot \nabla f > \|\nabla f\|

So∥v∥∥∇f∥cos⁡(θ)>∥∇f∥\|\mathbf{v}\| \|\nabla f\| \cos(\theta) > \|\nabla f\| Since v\mathbf{v} is a unit vector, ∥v∥=1\|\mathbf{v}\|=1 and cos⁡(θ)≤1\cos(\theta) \leq 1.⇒⇐\Rightarrow \LeftarrowThus, ∇f\nabla f is in the direction where ff increases the fastest.