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Evangelos Kazakos

@ekazakos.bsky.social did:plc:u73ld57pmwsta45y45uitdfi

Postdoctoral researcher @ CIIRC, CTU, Prague working in vision & language. Also robotics noob. PhD from University of Bristol. Ex. Samsung Research (SAIC-C). I love coffee and plants. And socks. 𖤓꩜𓆉𓃰𖤐

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Evangelos Kazakos (@ekazakos.bsky.social) é um usuário do Bluesky desde 2 setembro 2024. Tem 1.046 seguidores, segue 762 contas e publicou 1.729 posts.

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  • Mark Riedl@markriedl.bsky.social

    Aside: In 2018 @matthewguz.bsky.social and I were playing around with direct manipulation of neural nets without backprop arxiv.org/abs/1802.03605. Didn't work super well, but the models were crude by today's standards. Fun to see things we were trying in 2018 might actually work quite well today.

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  • Mark Riedl@markriedl.bsky.social

    I'll also note that this appears to largely be one-shotting the weight edits. When combined with RL or evolutionary search loops, this should mean that specialized neural networks can be built without back propagation on data. This is where things will get really interesting.

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  • Mark Riedl@markriedl.bsky.social

    This is fascinating. Very large models can read the weights of small models and intuit what those models were trained to do, and make direct weight changes to improve them. rikiyat.github.io/blog/weight-...

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  • Chanda Prescod-Weinstein 🌌@chanda.blacksky.app

    I voted! With my Lula glasses in tow 🤩

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  • Ethan Mollick@emollick.bsky.social

    If this holds up, it is big: "We asked GPT-6 Astra to edit Qwen3.5-0.8B weights to improve math. It directly changed only 0.016% of weights, fixing 0.8B's reasoning loops & improving math up to 6x and even instruction following 3x, without gradients or training." rikiyat.github.io/blog/weight-...

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