New (2nd edition) at https://
amzn.to/4tULP1b RAG-Driven Generative AI — Build MAS-RAG with DualRAG, GraphRAG, multimodal video pipelines, and Oracle Database 23ai (=Oracle’s major database release that natively embeds artificial intelligence and vector search directly into its
@kirkdborne
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RAG-Driven Generative AI book, 2nd edition
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Hands-on guide to LLMs, agents and RAG in finance
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Large Language Models in Finance — Hands-on guide to LLM architectures, agents, RAG, governance and evaluation in finance: https://
link.amazon/B0dM4HogS v/ @PacktPublishing 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
🟢Understand LLM foundations for financial applications
🟢Build financial -
Book on Building AI Agents for Finance
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Awesome release from @PacktPublishing … "Building AI Agents for Finance: Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python" After receiving my copy of this 758-page monster book, my first reaction was that it is so amazing.
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Dots: OpenAI’s 24/7 AI computer on GPT-6 Astra
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Dots – explained by @beamnxw : “Dots is a computer with memory that works 24/7. OpenAI launched it Sept 29 2026 on GPT-6 Astra. Each Dot has its own cloud computer and browser, reaches 4,000+ apps, keeps context across ChatGPT, Slack and Teams, and learns what good looks like
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Jev: fast decision layer for AI agents
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Jev — The fast decision layer that makes AI agents cheaper, faster, and easier to control — by @0xwhrrari
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Graph Engineering: Running 1,000 AI Agents in Parallel
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Graph Engineering: How to Run 1,000 AI Agents in Parallel From One Prompt — by @0xWast3
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Monetizable AI agent auto-responds to visitor comments
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Check this out … a swift monetizable AI Agent that auto-responds to visitors’ comments with something more interesting and useful for your social post’s readers …
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Course Selection Targets Statistics Skills for AI
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12 Best Statistics Courses in 2026 (Ranked by What You Actually Need, for AI) — list compiled by @tut_ml in the quoted post below ⤵️
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Machine Learning Definition and Tom Mitchell’s Foundational Quote
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Learn from Experience! — the key to success in life and in Machine Learning. "Machine learning is the study of computer algorithms that automatically improve with experience." — From the first page of Tom Mitchell's book [1997]: https://
cs.cmu.edu/~tom/files/Mac
hineLearningTomMitchell.pdf
… My paraphrase: "ML is the -
Deep Learning with C++: Neural Networks Using CUDA
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Deep Learning with C++ — Design and deploy neural networks using CUDA for high-performance AI in C++ Get the book at https://
amzn.to/4nzdKB4 from @PacktPublishing @PacktDataML