this post was submitted on 07 Oct 2026
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More accurately:
>looks inside
>matrix multiplication
Max(input*weights, 0) is an if in a sense, I guess.
Good old ReLU. I've heard that CNN's perform better when using ReLU as the activation func, and that's probably why; ReLU acts as a filter on the image's features.
Nah. Without a nonlinearity you just get a linear combination of inputs instead of the output of a deep neural network. ReLU or Ramp is just the simplest possible non linearity. Using a simple function can enable using deeper networks yielding even better performance.
It's actually somewhat of a headache, numerically. Works well enough tho.
Had one guy asking if AI is conscious. I said the whole thing is actually one very big excel sheet, so does he think that excel can be conscious? Anyway, I think the guy is now in a relationship with office.
Yes, it is inherently incorrect, I just think that increases the fun factor. It reminds me of that guy who wrote a prime-checker for his thesis and it was just a massive list of if-statement
98% accurate prime checker, super fast
isPrime() return False;
A transistor is on or off. It's all if-then.
No, it's more elemental: it's all ands , ors and nots
Boolean math let's you convert it all to nand gates. For ease of manufacturing this is what is done.
Matrix multiplication, activation functions and softmax. Also some matrix addition sometimes. That's literally it
Everything is quantum field fluctuations.
That's literally it.
I mean yeah, the mechanism itself is straightforward, but isn't a big thing that we don't really know what it chooses for its... basis vectors? Something like that, I don't do programming and I'm out of practice with matrices