2nd Edition, by @keithbourne v/ @PacktDataML "Unlocking Data with Generative AI and RAG — Learn AI Agent Fundamentals with RAG-powered Memory, Graph-based RAG, and Intelligent Recall" Get the book here: http://
amzn.to/49zsIkb
AI
-
New Book: Unlocking Data with Generative AI and RAG, 2nd Edition
By
–
-
New book on designing multi-agent AI systems with MCP and A2A
By
–
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 -
AI Agents, MCPs, and Container Safety Mechanisms
By
–
We use both together. In practice, for containers to be useful, you often have to punch some holes: GitHub, Anthropic API, kube, other MCPs. Auto mode makes interacting with these safer. It significantly reduces the risks of accidental data deletion, exfiltration, and prompt
-
Anthropic tops OpenAI in business adoption, but may not last
By
–
Anthropic just passed OpenAI in business adoption for the first time, 34.4% vs 32.3%, per Ramp's latest AI Index. But the same report that announces this spends most of its word count explaining why it probably won't last. Uber already blew through its entire 2026 AI budget. A
-
Anthropic Explores Microsoft Maia Chips for AI Cloud Compute
By
–
Anthropic explores Microsoft Maia chips for cloud compute https://
cloudcomputing-news.net/news/anthropic
-microsoft-maia-chips-cloud-compute/?utm_source=dlvr.it&utm_medium=twitter
… #Cloud #Automation #Data #Tech #RAG #AgenticAI #ExecutiveLeadership #Innovation -
Business Value of Agentic AI: Three Key Pillars
By
–
What's The #Business Value Of #AgenticAI? Three Key Pillars For Scaling #AIAgents
by Preetpal Singh @Forbes Learn more: https://
buff.ly/Ax4IOkO #LLM #GenerativeAI #ArtificialIntelligence #MachineLearning -
MeMo: Separate Memory Architecture for Language Models
By
–
Researchers just gave LLMs a separate brain for memory. Language models go stale the moment training ends. Updating them risks breaking what they already know. A new paper proposes MeMo. It pairs any LLM with a separate trained memory model. The base model stays frozen.
-
Boring context compaction beats multi-agent systems for most use cases
By
–
I've built multi-agent systems for clients. I still think they're overrated for most use cases. What's underrated is boring. Context compaction. The reason your AI app feels slow and expensive isn't the model. It's everything you keep stuffing into the prompt before it even
-
Request for publication of GPT-4 architecture to clarify water estimates
By
–
Given the scale of water estimates for the "bottle of water per generated email" that come from assumptions about GPT-4's architecture, it would be greatly in the interest of @OpenAI to publish the architecture of this now-retired, three-year-old model.
-
Agent Task Timing and Pricing Tier Strategy
By
–
Most agent tasks don't need to be fast. They need to be done by morning. A slow tier fits that reality well.