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
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.
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
More accurately:
>looks inside
>matrix multiplication
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.
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.
Matrix multiplication, activation functions and softmax. Also some matrix addition sometimes. 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
Everything is quantum field fluctuations.
That’s literally it.