The problem isn't an "everybody knows" kind of problem. People (myself included) are rolling our eyes because it's the most rube goldbergian way to say it.
It's analogous to saying that subtraction is a neural network. Addition and negation are core elements of modern state of the art neural networks, and you can express subtraction as a combination of those two modern neural network techniques. Therefore subtraction is a neural network.
The line in the article about the formula y = A x is illustrative:
> This [y = A x] should look familiar, because it is a neural network layer with no activation function and no bias.
Imagine that as:
> This [y = a + b] should look familiar, because it is a neural network layer with no activation function and no bias and no multiplication. Meanwhile, this [y = -x] should also look familiar, because it is a neural network layer with no activation function, no bias, no addition, and only negation.
You'd expect that kind of explanation of subtraction if someone had never learned about addition and negation outside of neural networks, but you'd roll your eyes and say it's just such a bizarre way to talk about addition, negation, subtraction, and neural networks.
It's analogous to saying that subtraction is a neural network. Addition and negation are core elements of modern state of the art neural networks, and you can express subtraction as a combination of those two modern neural network techniques. Therefore subtraction is a neural network.
The line in the article about the formula y = A x is illustrative:
> This [y = A x] should look familiar, because it is a neural network layer with no activation function and no bias.
Imagine that as:
> This [y = a + b] should look familiar, because it is a neural network layer with no activation function and no bias and no multiplication. Meanwhile, this [y = -x] should also look familiar, because it is a neural network layer with no activation function, no bias, no addition, and only negation.
You'd expect that kind of explanation of subtraction if someone had never learned about addition and negation outside of neural networks, but you'd roll your eyes and say it's just such a bizarre way to talk about addition, negation, subtraction, and neural networks.