Eggplant.place

1y

#YGO #ARC-V #DL
https://x.com/YuGiOh_DL_INFO/status/1846883502752780669
10/23！！！！！回來了！！！！！遊里！！！！

6 0 0 View Post & Replies See Original

1y

#YGO #DL #ARC-V

蛤等等遊矢&柚子真的是一個系列，真的有紀念活動，然後這架勢年末真的可以札克落下 Merry Zarc Xmas 了吧，蛤？？？
突然大過年？？？

3 0 0 View Post & Replies See Original

102d

#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……

13 0 0 View Post & Replies See Original

63d

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?

#ai #programming #DL

Edited 63d ago

0 0 0 View Post & Replies See Original

63d

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

#peertube

The new LISPY GOPHER SHOW unix_surrealism banner, still not sporting someodd. You will see it eventually. 8UTC Sunday toobnix.org, Wednesday 0UTC anonradio.net.

ALT

Edited 62d ago

0 0 0 View Post & Replies See Original

56d

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.

#ai #programming #dl

0 0 0 View Post & Replies See Original

60d

#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.

LISPY GOPHER SHOW

anonradio.net every 000UTC

unix_surrealism; the gopher and lisp alien wade through flooded wreckage helped by two demons.

ALT

Edited 60d ago

0 0 0 View Post & Replies See Original

43d

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

Χᵩᵢ = TPᵩⱼ + TNᵩⱼ − FPᵩⱼ − FNᵩⱼ, 𝑗≠𝑖

of the 𝑖th neuron at timestep 𝑛. Next

Yᵩᵢ = P( Χᵩᵢ + ξᵩᵢ ) − P( Χᵩᵢ − ξᵩᵢ ), using P for the

ALT

0 0 0 View Post & Replies See Original

15d

https://lispy-gopher-show.itch.io/dl-roc-lisp/devlog/1465107/shark-restaurant-dl-roc-dot-lisp-explained-deep-learning-receiver-operating-characteristic-part-2-simple-version

#itchio #gamedev #programming #theory completely explainable game-embeddable #deepLearning system using #roc #statistics .

I coded this one simply and iteratively, since a few people worked on reimplementing my #commonLisp code to-be-simpler.

The gist is that I show that deep learning updates, and indicate training as well are a simple true-positive/true-negative/false-positive-false-negative equation of the previous time step in an eminently explorable way. #DL #AI