A derivative is a function, so you can differentiate it again. Nothing new: it's the same machine, run twice.
Episode 9's car, continued. s[t] = t³ − 6t² + 9t on top, velocity in the middle, acceleration at the bottom, and one playhead through all three. Each panel is the slope of the one above it. Position is where you are, velocity is how fast and which way, and acceleration is the push you feel in your back.
The moment to watch is t = 1. The car is stopped, so velocity is zero, but acceleration is −6. It's still being pushed backward. Velocity zero doesn't mean acceleration zero. A little later the car is reversing with negative acceleration and getting *faster*, because negative acceleration doesn't mean slowing down. Same signs, speeding up. Opposite signs, slowing down.
The second derivative also shapes the curve. Where s″ is negative the graph bends downward, where it's positive it cups upward, and where s″ changes sign the bend flips. That's concavity, and episode 25 goes all the way into it.
Notation: f′, f″, f‴, then f⁽⁴⁾. In Leibniz, d²y/dx². The 2s count how many times you differentiated. Nothing is squared.
|
Learn how to test your Android apps on p...
Everyone's spinning up AI, but how do yo...
So what even is a token? Well, in this c...
Help your AI agents generate better code...
Discover the latest updates to Android C...
We are talking to the NFL about their in...
Gayatri built a custom journaling device...
What does it take to run AI in productio...
Using Nano Banana and Gemini through Ant...
In Flutter 3.47, Flutter Widget Previewe...
Chrome makes it easy to see CSS specific...