Neat AI does Neat XOR Gen 0

[@martinagnardahl]

Great video (as usual), very detailed and can be applied also to other types of NN. Enjoyed especially part about visualization of NN. Can't wait for part 2 with details about speciation. Thanks!

[@neatai6702]

Awesome, thank you!

[@pojeby]

only 1k views? this deserves waaaay more

[@sb8300]

looking forward for part 2!

[@neatai6702]

working on it now.. it'll focus on speciation..

[@Mplays-os8so]

brilliant content, thank you :) so neat!

[@neatai6702]

Glad you enjoyed it!

[@raciociniologico1378]

You can implement that with graph implementation?

[@firespark804]

This is a nice explaination. In to intro, some of the shown networks seem to converge to a fitness of 3, mainly because it is giving a rather high value for the input (0,0). I'm cuurently facing the same issue in my implementation of NEAT. Do you have ideas to why this issue could occur? Thanks!

[@stephenlavender8781]

How did you implement the lookup table? I was trying to recreate NEAT in python and I m a struglling to create it. How did you do it and can you think of a Python way do it as I understand you might have not used Python?

[@tiagotiagot]

Maybe the disabled ones could be faint semi-transparent, so you can see them if you try hard enough but they're not distracting most of the time?

[@rpraver1]

Why no code?

[@Kraus-]

What is the application of solving XOR?

[@fappylp2574]

It's been an unsolved problem for many years now. With modern AI tech we might be able to find a stable solution to XOR, which is predicted to lead to many advances in science and industry.

[@freddiebobbin9616]

@@fappylp2574 Just wait until we solve the half-adder ...

[@PowerfullPillow]

Uumpf bit of an overkill don't ya think?

[@JeSuisJedi]

Awesome o/

[@samjanssens1509]

is your code available on github or anything ? thx

[@teenspirit1]

I did all this, but evaluating mnist takes too damn long.