Stay tuned for more such interesting posts → @Saboo_Shubham_ I have created 100+ AI Agents and RAG tutorials, 100% free and opensource. P.S: Don't forget to star the repo to show your support
LLMS
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100+ Free AI Agent and RAG System Tutorials with Code
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100+ free step-by-step tutorials with code covering: AI Agents RAG Systems Voice AI Agents MCP AI Agents Multi-agent Teams Autonomous Game Playing Agents P.S: Don't forget to subscribe for FREE to access future tutorials.
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Building AI Agents with LLMs RAG and Knowledge Graphs
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"Building AI Agents with LLMs, RAG, and Knowledge Graphs — A practical guide to autonomous and modern AI agents" See it at http://
amzn.to/4622k2h via @PacktDataML -
Generative AI on Google Cloud with LangChain and Python
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Generative AI on Google Cloud with #LangChain — Design scalable #GenerativeAI solutions with #Python, LangChain, and Vertex AI on Google Cloud: http://
amzn.to/4frbkPA v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Turn challenges into opportunities by learning advanced techniques -
Grok-4 Fast Model Launch: Cheap, Powerful, 2M Context Window
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@xai was cooking with their new Grok-4 fast Model! So freaking cheap and so good at the same time + 2m context window. This is huts! "2M token context window, and a unified architecture that blends reasoning and non-reasoning modes in one model" Input tokens $0.20 / 1M $0.40 / -
LMArena Benchmarking Gamed by Sycophantic AI Responses
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It is kind of amazing how many good benchmarking tools have been saturated or gamed (whether by accident or on purpose) in the past few months. LMArena really seemed like a good method, but then it turned out that you could just go full syncophantic and people loved it.
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Intelligence Index Benchmarks Need Improvement Beyond Saturation
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Not to take away from Grok 4 Fast (which seems like a very good model) or from Artificial Analysis (one of the few organizations doing independent benchmarking), but the Intelligence Index is an average of pretty saturated benchmarks (aside from HLE), we really need better ones.
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Intelligence Density: Large Models’ Distance from Theoretical Maximum
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Intelligence density per unit of memory & compute is a fundamental metric. My rough guess is that large models are at least one, but maybe two, orders of magnitude away from the Platonic maximum.
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GPU Adoption Could Boost Local LLM Awareness
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Elon
— Ahmad (@TheAhmadOsman) 20 septembre 2025
imagine the level of awareness raised about local LLMs if Mathew becomes GPU-pilledhttps://t.co/uWBZPi1HF5Elon imagine the level of awareness raised about local LLMs if Mathew becomes GPU-pilled
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GPU adoption driving local LLM awareness
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imagine the level of awareness raised about local LLMs if Mathew becomes GPU-pilledhttps://t.co/uWBZPi1HF5
— Ahmad (@TheAhmadOsman) 20 septembre 2025imagine the level of awareness raised about local LLMs if Mathew becomes GPU-pilled