#YGO #ARC-V #DL
https://x.com/YuGiOh_DL_INFO/status/1846883502752780669
10/23！！！！！回來了！！！！！遊里！！！！
dl
#YGO-ZEXAL #DL
https://x.com/punsukabooks/status/2003370537360457749
謝謝梅拉古落地……梅拉古跟Ⅳ在動畫沒講過話的遺憾在DL實現了……
A better and #symbolic #deeplearning #algorithm in #commonLisp .
https://screwlisp.small-web.org/fundamental/a-better-deep-learning-algorithm/
I hope I come across as slightly tongue-in-cheek! Though all my points and notes are in fact genuine.
tl;dr I define completely explainable and interpretable deep learning / inferencing in terms of operations on sets of symbols.
I think it successfully underscores the wild misapprehensions about deep learning that abound in the wild. What do you think?
Edited 22d ago
https://toobnix.org/w/9oA5WZEkbjKkfbsSxEoJ8v #archive
Okay I guess on the hour it's the Sunday-morning-in-Europe #lispyGopherClimate .
a. I will lightly go over my recent #commonLisp #symbolic #DL ( #ai!) algo / article.
b. Excitingly that gave me occasion to use
(this-function foo &rest keys &key &allow-other-keys)
which I used to pass data-like parameters along without cluttering up arguements (waters' functions of seven arguments). People had tried to explain it to me previously but now I underst
Edited 21d ago
As someone who now has a feedforward neural network of a single hidden layer implementation (in #commonLisp) I learned a lot about what has a spot to be stuck into the algorithm.
https://screwlisp.small-web.org/fundamental/sharpsign-sharpsign-input-referential-ffnn-dl-data/
Something that turns out to be easy to stick in is making training data which copies data out of the current context or even to simply point the training data definition into the #deepLearning inference input context though I did not prove convergence for the latter case.
#lispyGopherClimate #lisp #technology #podcast #archive, #climate #haiku by @kentpitman
https://communitymedia.video/w/c3GdAXe7BQTbK3VrcXCm7E
& @ramin_hal9001
On the #climate I would like to talk about the company that found #curl and #openssl's #deeplearning many (10ish) 0-day vulns "using #ai ". (#llm s were involved).
This obviously relates to my #lisp #symbolic #DL https://screwlisp.small-web.org/conditions/symbolic-d-l/ (ffnn equiv). Thanks to everyone involved with that so far.
I implemented that using #commonLisp #condition handling viz KMP.
Edited 19d ago
Yeesh, okay it is out and I can stop telling you I am going to write it.
https://screwlisp.small-web.org/complex/lisp-feedforward-deep-learning-example/
#deepLearning #symbolic #ffnn pure ansi #commonLisp
The example deliberately causes a hallucination programmed into the training data via simple #roc reasoning. To my knowledge the ROC interpretation of ffnn inference is original to me, here.
The hallucination is in both lockstep and single #neuralnet activations.
Be the first to complain my #DL works on subregions of jagged lists! #programming
