It's not to be indexed the goal of an llms.txt it's to be executed #GEO #SEO but if it's crawled, it's a starting point.
LLMS
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LLM Training: RL vs SFT with In-Context Learning
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"Don’t be difficult. I mean this is obvious." Sutton is right ofc. The analogue in LLM land to what humans do is something along the lines of: Given this math problem AND human example solution in the context, solve the problem. Reward of 1 if correct. It's not SFT, it's RL.
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Multi-Agentic Models: Just One Model With Different Roles?
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what is a “multi-agentic model” though. isnt it just the same model wearing different hats
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Using ChatGPT to analyze podcast transcripts and AI content
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Something I am experimenting with. I copy pasted: 1) the full podcast transcript
2) the bitter lesson blog post
3) my full post above To ChatGPT. The interesting part is you can fork the conversation context to ask any questions and take it in whatever direction with chat: -
Claude ranks third: AI adoption contradicts anti-AI sentiment
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#3 now… only topped by Gemini and ChatGPT. Crazy how much anti-AI sentiment you see on socials when the actions of the general public show quite the opposite.
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ChatGPT and DeepSeek Define Public Perception of LLMs
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i now go to chat dot com for chatgpt i also know that llms will be forever known by the general public as chatgpt (or DeepSeek)
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Sutton’s Bitter Lesson Shapes LLM Research Approaches
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Finally had a chance to listen through this pod with Sutton, which was interesting and amusing.
— Andrej Karpathy (@karpathy) 1 octobre 2025
As background, Sutton's "The Bitter Lesson" has become a bit of biblical text in frontier LLM circles. Researchers routinely talk about and ask whether this or that approach or idea… https://t.co/EQ4snNmiTMFinally had a chance to listen through this pod with Sutton, which was interesting and amusing. As background, Sutton's "The Bitter Lesson" has become a bit of biblical text in frontier LLM circles. Researchers routinely talk about and ask whether this or that approach or idea
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DeepEval: Open Source LLM-as-Judge Evaluation Framework
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Evaluate multi-turn conversations with just a few lines of code! DeepEval lets you build decision-tree based LLM-as-a-judge evals that break down complex chats step by step. 100% Open Source.
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LiquidAI releases LFM2-Audio-1.5B model on Hugging Face
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It's also available on @huggingface to download it. You can use our user-friendly liquid-audio pip library. https://
huggingface.co/LiquidAI/LFM2-
Audio-1.5B
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