Matrix multiplication, activation functions and softmax. Also some matrix addition sometimes. That’s literally it
Comment on no one can understand AI
LouNeko@lemmy.world 22 hours ago
More accurately:
>looks inside
>matrix multiplication
glibg10b@lemmy.zip 19 hours ago
Viceversa@lemmy.world 17 hours ago
Everything is quantum field fluctuations.
That’s literally it.
Epzillon@lemmy.world 18 hours ago
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
weps@lemmy.world 17 hours ago
98% accurate prime checker, super fast
isPrime() return False;
Rhaedas@fedia.io 18 hours ago
A transistor is on or off. It's all if-then.
Viceversa@lemmy.world 17 hours ago
No, it’s all ands , ors and nots
nop@lemmy.world 16 hours ago
Boolean math let’s you convert it all to nand gates. For ease of manufacturing this is what is done.
Gladaed@feddit.org 21 hours ago
Max(input*weights, 0) is an if in a sense, I guess.
mrchampion@lemmy.world 19 hours ago
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.
Gladaed@feddit.org 19 hours ago
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.