In general, differentiating a function is a lot easier than integrating one.

Because functions can be written in multiple ways (simple example: ‘x+1’ vs ‘1+x’. For harder examples, see for example https://en.wikipedia.org/wiki/List_of_trigonometric_identiti...), it may still be difficult to prove that the derivative of a proposed integral of some function f is equal to f, but most of the time, checking a proposed solution to ".

That reminds me of a joke that goes something like this:

> Me: What is 2+2?

> AI: It’s 42.

> Me: Wrong, it’s 4. What’s 2+3?

> AI: It’s 4.

Can someone explain me the joke

AI (or more accurately, machine learning (ML)) learns by being told when it’s wrong and right (like a child). The AI makes a mistake on what 2+2 is, so it’s corrected. However, when it’s asked 2+3, it doesn’t know that 3 is one more than 2, and the only answer it’s learned is 4, so it says 4.

As is well known, a child learning language will often initially assume that rules/patterns are more regular that they actually are.

The ai was trained that the answer is 4, so the second time around it went with 4.