Chill and problem prone (though all of them are overcome) #CommonLisp #lisp #video exhibiting my #binryhop hopfield net package.
https://forth.noip.me:8443/w/23cQQJVTcG6nqsnT8jkgWV

So chill that my package relaxes a lot of constraints on hopfield nets (sure, it can be jagged, rewritable memories, and the memory can be NIL, and the memory can be a subset of of the input or vice versa (????)
About a half hour; would probably be quite good at 1.5x speed.

Example of debug noodling around in a lisp package a bit.

#CommonLisp #Gopher #binryhop #deepNetworks #asdf #lisp
gopher://tilde.institute/1/~screwtape/binry-hop/
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+312f7e7363726577746170652f62696e72792d686f702f
gopher://gopher.club/1/users/screwtape/
https://gopher.floodgap.com/gopher/gw.lite?=gopher.club+70+312f75736572732f7363726577746170652f

I was redeveloping my nascent binry-hop deep hopfield network package to use package-inferred-system, so different sorts of components and data (book)? can be cooked into one overarching system but loaded separately.

I'm happy with it; and I believe in using asdf strongly idiomatically. Commentary?

#binryhop Hopfield net #deepLearning book rough chapter 1
#gopher phlog about it:
tilde.institute/0/~screwtape/209661045-rough-chapter-1
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+302f7e7363726577746170652f3230393636313034352d726f7567682d636861707465722d312e747874
Chapter 1:
gopher://tilde.institute/0/~screwtape/binry-hop-book/01-autoassociative-memory.txt
https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+302f7e7363726577746170652f62696e72792d686f702d626f6f6b2f30312d6175746f6173736f636961746976652d6d656d6f72792e747874
tl;dr it's the iconic deep learning XOR example, using a hopfield-net-closure-generating common lisp package (at https://gopher.floodgap.com/gopher/gw.lite?=tilde.institute+70+312f7e7363726577746170652f636c2d62696e72792d686f702f )
It's at the top of my phlog.

Help me form my book-writing and deep-learning!