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lispybanana

1,405 カルマ登録 9 年前


    (cons 6 (cons 6 (cons 6 '())))
if you can read this, the cdr fell off

投稿

Oatmeal Spice: Interesting Procedurally Generated Output

boristhebrave.com
1 ポイント·投稿者 lispybanana·6 日前·0 コメント

Selling My House with a Chatbot

nytimes.com
1 ポイント·投稿者 lispybanana·24 日前·0 コメント

Basics of Film Financing

theentertainmentexpert.com
1 ポイント·投稿者 lispybanana·2 か月前·0 コメント

Time-Locked Cryptography

farlow.dev
4 ポイント·投稿者 lispybanana·5 か月前·1 コメント

[untitled]

1 ポイント·投稿者 lispybanana·7 か月前·0 コメント

Tragic Algebra of Stock-Based Compensation

michaeljburry.substack.com
1 ポイント·投稿者 lispybanana·7 か月前·2 コメント

コメント

lispybanana
·7 か月前·議論
Open-access article
lispybanana
·7 か月前·議論
See here instead (open article):

<https:// open.substack.com/pub/michaeljbu rry/p/foundations-...>
lispybanana
·8 か月前·議論
Nicely done.
lispybanana
·8 か月前·議論
Would they have diagnosed an issue if you hadn't presented it to them?

Life solves problems itself poses or collides with. Tools solve problems only when applied.
lispybanana
·9 か月前·議論
How does NN create a concept not in its training data? (Does it explore negative idea-space?) What if a concept uses a word not yet invented? How does LLM produce that word and what cosine similarity would such a word have if it's never appeared next to others? How would we know if such a word is useful?
lispybanana
·9 か月前·議論
Humans do this but this is not all they do. How do we explain humans who invent new concepts, new words, new numerical systems, new financial structures, new legal theories. These are not exactly predictions (since they don't exist in a training set) but they may be composed from such sets.
lispybanana
·2 年前·議論
Discouraging, sure, but now the real question: did you apply anyway? :) I hope you did!