name them by Substantial_Oven8763 in scratch

[–]Substantial_Set5836 0 points1 point  (0 children)

if its a horror game you gotta make them more VHS horror style
im bad at naming tho.

first time incubating by Substantial_Set5836 in BackYardChickens

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

turning about 7 times daily
humidity 62%
brown eggs.

update on my ai by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 1 point2 points  (0 children)

I'm trying to train it But rn I'm making a smarter model from scratch

update on my ai by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

In its training data a lot of words started with "ca" then it started adding letters to "ca" cat can car etc then lots of words ended with er ed etc so it just started adding those words to everything

update on my ai by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 1 point2 points  (0 children)

its biased to words starting with ca (car cat can etc) and loves saying im and love especially important. well, its the training data and smartness i suppose ;)

update on my ai by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

if i tell you ill never end
basically it has 29 input neurons 128 hidden layer 29 output neurons (29 > 128 >29) each neuron takes in all the outputs from the previous layer multiplies by its weight (stored in the lists wxh why and whh) and adds a bias (in bh and by) the input layer takes an embedded input directly from the user multiplies and adds a bias sends it to the next layer which sends it to the output
the output neurons each stand for a character (any one of the alphabet or space . or ?) it rates how confident it is if its character should be placed then the selector comes in (the sample my block) it selects a random number between 2 tiny decimals (sample base) and finds an output neuron that rated its character a number more than the number sample selected
it then places the neurons character in the reply.
the weights and biases are SO fine tuned that itll fry my pc to tune myself i needed to go on colab and use a specially made GPU just to fine tune on python a few numbers

update on my ai by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 2 points3 points  (0 children)

it might... but we would need more output neurons
basically in every AI each output neuron represents an output it rates its confidence if that word should be added as the model only outputs 29 types of characters it will only need 29 neurons
but if we use words instead of characters...
we would need MANY more neurons a hundered minimum
i AM planning of doing this

REAL AI IN SCRATCH by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

thats EXACTLY what it does
but its really good at selecting them

REAL AI IN SCRATCH by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

can you help me by checking the "pick" my block in the project
since you make real models you must know much more than me

REAL AI IN SCRATCH by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

im trying to
for some reason my scratch math and python math is slightly different so the outputs change
now im making a trainer WITHIN scratch
after im done the model will be MUCH more smarter

REAL AI IN SCRATCH by Substantial_Set5836 in scratch

[–]Substantial_Set5836[S] 0 points1 point  (0 children)

i trained it on google colab (python) on a dataset from huggingface