UNBELIEVABLE RESOURCE The bible for understanding LLMs is NOW AVAILABLE online to read (FOR FREE) Covers all the concepts below, no experience needed and anyone from any background can understand it – Tokens / Tokenizers
– Transformers
– Attention
– KV Cache
– Prefill vs
LLMS
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Free online book covers LLM concepts for all backgrounds
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LLM Ideation: Coherence vs. Availability Trade-off
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The key distinction here is worth sitting with: Standard LLM ideation can be coherent but available. Random recombination can be unavailable but incoherent. The target is the rare quadrant: coherent but unavailable. That is where this paper gets interesting.
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Paper highlights rare ‘coherent but unavailable’ LLM outputs
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The key distinction here is worth sitting with: Standard LLM ideation can be coherent but available. Random recombination can be unavailable but incoherent. The target is the rare quadrant: coherent but unavailable. That is where this paper gets interesting.
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New preprint explores the frontier of what is thinkable
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Science has a hidden frontier. Not the frontier of what is true. The frontier of what is thinkable. A remarkable new preprint by Alejandro H. Artiles, Martin Weiss, Levin Brinkmann, Iyad Rahwan, Bernhard Schölkopf, Christopher Pal, Hugo Larochelle, Anirudh Goyal, and Nasim
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Apology and warning: learn local LLMs to avoid rug pulls
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I am sorry man, I keep telling people they must learn how to run LLMs locally and be ready to get rugpulled at any moment by these companies
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AI Transitions from Token Maximization to Cost Efficiency
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We are transitioning from the intelligence/tokens maximizing era to the cost efficiency optimization era.
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Free online LLM bible: Understand ChatGPT, run models at home, future AI careers
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DROP EVERYTHING The bible for how LLMs work is now available online to read FOR FREE This is for you if you: – Want to run these LLMs at home on your hardware?
– Want to understand how ChatGPT works?
– Want to work at an AI Lab in the future? Covers all the concepts from -
LLMs should aid human learning, creativity, and experimentation
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I feel that the trend towards training models to autonomously go off and try to do everything themselves is anti-human. We should, IMO, be training LLMs to support humans in their learning, creativity, and iterative experimentation.
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Inquiry about safetensors version availability vs ggufs
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Do you have a safetensors version published or only ggufs?
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Anthropic engineers’ token-saving habits, no setting changes needed
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this guy literally breaks down the exact habits Anthropic engineers use to save millions of tokens without changing a single setting 🤯
— Charly Wargnier (@DataChaz) 22 mai 2026
Watch the video, then bookmark the written guide 👇 https://t.co/gAHjGmFxwy pic.twitter.com/Hlb96srixBthis guy literally breaks down the exact habits Anthropic engineers use to save millions of tokens without changing a single setting Watch the video, then bookmark the written guide