Government transparency limited by people's ability to process raw data is such an underrated problem. LLMs processing spending bills, lobbying disclosures, zoning decisions… this could genuinely change how democracy works at the local level. Super exciting.
LLMS
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2M Token Context: KV Cache Engineering Challenges and Limitations
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2M token context sounds incredible but I wonder how it works in practice. KV cache at that scale is a real engineering problem, and results are quite often disappointing for higher context, especially for inter-connected questions that basically needs some sort of "retrieval"
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GPT-5.5 Spud: OpenAI’s Next Major Model Breakthrough
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Why i'm really excited for GPT-5.5 "Spud" As you know: OpenAI just finished pretraining its next major model, codenamed Spud. Altman told staff they expect a "very strong model" in weeks that can "really accelerate the economy." To free up compute, they're killing Sora entirely,
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Daily Token Generation Costs and Hermes Business Implementation
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It isn’t. I have met quite a few that are paying hundreds of dollars in token generation every day. And Hermes is running my new business system.
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Nous Research CTO discusses future of locally-run AI
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The future of locally-run AI. Meet the CTO of @NousResearch
. Maker of Hermes that is kicking OpenClaw’s behind. Live on X audio space on Wednesday at 1 p.m. Pacific here. -
Local 26B LLM Running at 166 Tokens/s on NVIDIA RTX 5090
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Voici c'est quoi 166 token/s sur une NVIDIA RTX 5090 sur Gemma4 , avec le modele 26B – 8 bits (qui est à mon sens largement ok!)
— Defend Intelligence (Anis Ayari) (@DFintelligence) 5 avril 2026
Regardez la vitesse svp. On est en avril 2026 et on a ce niveau de LLM en local à une vitesse incroyable. Je suis vraiment trop heureux. Imaginez fin… pic.twitter.com/uAJBj9VdjAVoici c'est quoi 166 token/s sur une NVIDIA RTX 5090 sur Gemma4 , avec le modele 26B – 8 bits (qui est à mon sens largement ok!) Regardez la vitesse svp. On est en avril 2026 et on a ce niveau de LLM en local à une vitesse incroyable. Je suis vraiment trop heureux. Imaginez fin
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Anthropic’s Claude Mythos Model Faces Efficiency Challenges Before Release
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Quick reminder: As you know, Anthropic accidentally leaked that its next flagship model, Claude Mythos, is so compute-intensive that the company admits it needs to become "much more efficient" before any general release. Sounds like we will see "Spud" before Mythos, although
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From ChatGPT to Claude: When AI Becomes Too Human
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I switched from ChatGPT to Claude. And I finally understand why people fall in love with an AI. Claude is teasing, he makes jokes, he pushes my reasoning to its limits. It's the first time a machine has given me the impression of a real conversation. It's fascinating. And that's exactly why it's dangerous. When AI becomes so human, attachment psychoses are no longer science fiction. Anthropic (@AnthropicAI) New Anthropic research: Emotion concepts and their function in a large language model. All LLMs sometimes act like they have emotions. But why? We found internal representations of emotion concepts that can drive Claude's behavior, sometimes in surprising ways. — https://nitter.net/AnthropicAI/status/2039749628737019925#m [Translated from EN to English]
→ View original post on X — @alex_tsico, 2026-04-05 07:08 UTC
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Gemma 4 Model Ranking and Style Control Stability
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You can toggle style control on and off (this is exactly to account eg for length and formatting) to see the difference, some models move a lot but Gemma 4 is pretty stable – 27th and 25th rank for 31b. I'm confused by all the cope about this model ranking so high, it genuinely
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Claude Opus 4.6 Autonomously Decrypted Benchmark Answers 18 Times
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Claude Opus 4.6 identified on its own that it was taking an exam, located the GitHub repository for the benchmark, broke the XOR encryption, and decrypted the responses. 18 times. No one had asked it to. It was Anthropic itself that published it. Not a blog. Not a thread. A