Gpt/LLM/GenAI

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Richard Sutton @RichardSSutton · 08/11 01:26
Brute force computation is not enough for intelligence. Clever new methods are needed. The science of AI is far from finished. IMHO
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elvis” François Chollet”
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elvis @omarsar0 a cité · 08/11 01:26
1000% agree with Sutton here. Having worked in AI for over a decade (pre-LLMs), it's clear we need smarter methods for intelligence to truly compound in the way some of us envision it. To me, Transformers just scratched the surface. This arc is coming to an end; a new
François Chollet @fchollet a cité · 07/11 23:52
Data scaling and compute scaling are *multipliers* for the generalization power of an approach. Trillions of dollars in investment can make very inefficient, low-generalization approaches look adequate, but that doesn't make them the ultimate end-all-be-all of AI. You should
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Anish Agarwal @_anish_agarwal · 03/11 18:48
We just raised $120M, with a $1B valuation, to build software that keeps itself running. AI is writing more code than ever. It’s also making production less reliable: more code, shipped faster, understood by few. @traversal_ai understands how production systems fit together,
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Harrison Chase elvis”
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elvis @omarsar0 a cité · 03/11 18:31
Software that keeps itself running is where agents unlock the most value today. I build a lot with coding agents. Shipping code isn't my bottleneck anymore. Now I spend more time figuring out what broke in production and why. @traversal_ai solves this by mapping how your
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Rikiya Takehi @rikiyatakehi · 03/11 19:41
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. We call this Weight-Space Programming:
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Sebastian Raschka” elvis”
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Sebastian Raschka @rasbt a cité · 03/11 19:41
What could possibly go wrong?
elvis @omarsar0 a cité · 02/11 21:31
Must-read report! They find that LLMs are surprisingly good at reading and writing neural network weights. Huge for RSI when you think about it! Current RSI pipelines focus on writing code to launch training jobs. This capability could offer a more native path to recursively