New release from @PacktDataML available at: http://
amzn.to/40Sp4O9 "Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Python-based Agentic AI Framework with tool use, memory, and multi-agent workflows" Table of Contents:
Introduction to Generative AI and AI
GENERATIVE AI
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New Technical Guide to Designing Multi-Agent AI Systems with MCP
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Guide to Building Production-Ready AI Agent Systems
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30 Agents Every AI Engineer Must Build — Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML —
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
Enhancing Generative AI Systems with RAG Integration
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Unlocking Data with #GenerativeAI and RAG — Enhance Generative AI systems by integrating internal data with large language models using RAG: http://
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Practical Guide to Building AI Agents with LLMs and RAG
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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 -
Building an AI-Powered File Reader using RAG and LLMs
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RAG with LLM: Creating an AI-Powered File Reader! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
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Announcing Agentic Generative AI for Autonomous LLM Systems
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Announcing Agentic Generative AI to Build Autonomous AI Systems with LLM! @SantaClaraUniv #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless
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Scaling 48 Stack Language Model for Zero Shot Learning
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GPT XL: Scaling 48 Stack Language Model for Zero Shot Learning! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming
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Annotation sémantique 3D en temps réel avec IA
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Semantically annotating 3D gaussian splats on the fly using gemini 3.1 + sparkjs
— Bilawal Sidhu (@bilawalsidhu) 15 mai 2026
1. Load any 3D scene and hit scan
2. Get 2D detections from VLM
3. Cluster outputs & project into 3D world space
4. Save as a persistent 3D semantic layer
Inspired by @alexanderchen's experiments… pic.twitter.com/CKZzpRkKtpSemantically annotating 3D gaussian splats on the fly using gemini 3.1 + sparkjs 1. Load any 3D scene and hit scan
2. Get 2D detections from VLM
3. Cluster outputs & project into 3D world space
4. Save as a persistent 3D semantic layer Inspired by @alexanderchen
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Second Scaling Law: Thinking tokens boost LLM performance without plateau
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The Second Scaling Law remains undefeated. If you want better hacking (or math, or science, or crossword puzzle solving) out of an LLM, just add thinking tokens. There doesn't seem to be any plateau so far.
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User shares experience with AI tools and building a site with an AI reader
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Love it! AI is a trip. I'm using Levangie Labs, which sits on top of Anthropic and OpenAI and greatly improves them. The best in AI is here: https://
x.com/i/lists/195353
6336675365173?s=20
… I have 50,000 in my lists now in AI: https://
x.com/scobleizer/lis
ts
… My AI reads all those to build my site. Oh,