A new way to fine-tune LLMs just dropped

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2026-04-28 04:47:59
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bycloud

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Evolution strategies were once seen as too inefficient for modern deep learning, but new LLM fine-tuning research has found a way to bring it back from the museum. This video explains how scalable evolutionary strategies could be for LLMs, and its latest developments.

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[OpenAI paper] https://arxiv.org/abs/1703.03864 
[Evolution Strategies at Scale] https://arxiv.org/abs/2509.24372
[EGGROLL] https://arxiv.org/abs/2511.16652 



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This video is supported by the kind Patrons & YouTube Members: 
πŸ™Spam Maj, Alex, Chris LeDoux, DX Research Group, Poof N' Inu, Deagan, Robert Zawiasa, Ryszard Warzocha, Tobe2d, Louis Muk, Akkusativ, Kevin Tai, Mark Buckler, NO U, Tony Jimenez, Γ‚ngelo Fonseca, jiye, Anushka, Asad Dhamani, Binnie Yiu, Calvin Yan, Clayton Ford, Diego Silva, Etrotta, Gonzalo Fidalgo, Handenon, Hector, Jake Disco very, Michael Brenner, Nilly K, OlegWock, Daddy Wen, Shuhong Chen, Sid_Cipher, Stefan Lorenz, Sup, tantan assawade, Thipok Tham, Thomas Di Martino, Thomas Lin, RichΓ‘rd Nagyfi, Paperboy, mika, Leo, Berhane-Meskel, Kadhai Pesalam, mayssam, Bill Mangrum, nyaa, Toru Mon, Lame Plane, Matej Macak, Len Mo, saylikhapekar, ZyanSheep, THEVIERAOS, Ricardo Raphael Corona-Moreno


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Archived Files

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Transcripttranscript.txt17.7 KBβ€”
File687comments.json50.3 KBβ€”

Total Size: 97.7 MB

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Archive ID687
Link ID687
Created At2026-04-28 04:47:19
Statuscomplete
Retry Count0
Is NSFWfalse
Content Typevideo
Link Info
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Normalized URLhttps://www.youtube.com/watch?v=lLkE9w1NJs0
Domainwww.youtube.com
Last Archived At2026-04-28 04:48:00

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