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Yacine Mahdid

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@yacinelearning

(neuro/ai) I make technical deep learning tutorials 👺
Montreal Canada youtube.com/@deeplearninge… Joined January 2019
2K Following 31K Followers 19K Posts

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Yacine Mahdid Verified account @yacinelearning
ok guys I’m looking for your favourite agent-flavoured research ideas from 2026 to include in my review (with credit)
do comment them below

it can be blog article a thought you had an anon schizo thread everything goes
Yacine Mahdid Verified account @yacinelearning 6d
alright folks if you are in SF next week I'll be presenting a workshop at the AI engineering code summit really hope to see you there

we're going to sit down take a deep breath and review what the heck happened in 2026 with ai agents it's going to be a full hour bring snacks
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Yacine Mahdid Verified account @yacinelearning
the weight space programming blog is getting more constructive feedbacks reproductions and research ideas extension than any other concepts I’ve seen released in recent time
Neil Kale Verified account @neilkale 2d
[1/3] turns out you can teach a 35b model to weight-space program better than opus o_0

earlier this week, @rikiyatakehi and @jayden_teoh_ showed that astra can manually write neural networks to solve atari games, one weight at a time. they call this weight-space programming.

on the @trajectorylabs platform, @o__jerry__o and I post-trained 27b and 35b-a3b qwen models to write networks for atari games. we curated WeightProgramBench, a set of 322 simple games to teach models to manually write neural networks.

we combined 51 atari-style games with 266 games adapted from crisp-game-lib for training, holding out the 5 original minatar games (freeway, breakout, asterix, seaquest, space invaders).

on freeway, qwen-27b climbed from averaging 21.0 to 47.1 points **without ever training on freeway**, but still not quite at astra’s 63.9 points.
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