The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning
AGENTS
-
Causal Emergence Predicts Reward in RL Agents
By
–
-
Causal Emergence Alignment Hypothesis in Reinforcement Learning Agents
By
–
The Causally Emergent Alignment Hypothesis: Causal Emergence Aligns with and Predicts Final Reward in Reinforcement Learning Agents Federico Pigozzi, Michael Levin: https://
arxiv.org/abs/2605.06746 #AIAgents #ReinforcementLearning -
Anthropic training: building Claude agents from A to Z
By
–
Anthropic a publié une Formation complet de 2 HEURES sur la construction d'agents Claude.
— Jouhatsu | AI Influence Operator (@Jouhatsu_ai) 16 mai 2026
Animé par l'ingénieur qui construit Claude Code.
Gardez-la précieusement en Signet🔖
de A à Z : Structurer un agent qui se gère sans supervision. Lui donner accès au terminal pour… pic.twitter.com/3kAKAgkz79Anthropic a publié une Formation complet de 2 HEURES sur la construction d'agents Claude. Animé par l'ingénieur qui construit Claude Code. Gardez-la précieusement en Signet de A à Z : Structurer un agent qui se gère sans supervision. Lui donner accès au terminal pour
-
New Book on Generative AI, RAG, and AI Agents
By
–
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 -
Learning Model Context Protocol for Building Agentic Systems
By
–
Learn Model Context Protocol [MCP] with Python — Build Agentic Systems in Python with the new standard for AI Capabilities: http://
amzn.to/4njfsVM by @chris_noring v/ @PacktDataML 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
Understand the MCP protocol and its core components -
The Critical Need for Testing in AI Agent Development
By
–
Garry Tan just said the quiet part out loud: AI agents don’t need “vibes.”
They need tests.
Everyone is shipping AI into products and praying it doesn’t hallucinate, get manipulated, or confidently lie to users. That’s insane. iFixAI runs 32 tests on your deployed AI and gives -
How to Build Structured AI Agents
By
–
How to build AI agents • Define scope
• Structure inputs
• Add tools & reasoning
• Orchestrate agents
• Add memory & context Smart agents are structured systems, not just prompts. Via Giuliano Liguori (
@ingliguori
) #AI #AIAgents #GenAI -
Building Complex Multi-Agent Systems for Automation
By
–
🚨 AGENT SWARMS – BUILD COMPLEX APPS AND AUTOMATIONS
— Abacus.AI (@abacusai) 16 mai 2026
Combine Gemini 3.1 Pro, Opus 4.7 and GPT 5.5 to create complex multi-agent systems
Each agent excels at a particular task – coding, testing, mobile app, research and monitoring
Master agent orchestrates worker agents pic.twitter.com/mLvu0sNKjwAGENT SWARMS – BUILD COMPLEX APPS AND AUTOMATIONS Combine Gemini 3.1 Pro, Opus 4.7 and GPT 5.5 to create complex multi-agent systems Each agent excels at a particular task – coding, testing, mobile app, research and monitoring Master agent orchestrates worker agents
-
AI’s Next Interface Will Be Your Eyes, Not an App
By
–
AI’s next interface won’t be another app.
— Ronald van Loon (@Ronald_vanLoon) 16 mai 2026
It will be your eyes.
That sounds futuristic, but it is already becoming real with glasses that can see what you see, understand context, and respond in real time.
Here’s why that matters… pic.twitter.com/xWz71JluX7AI’s next interface won’t be another app. It will be your eyes. That sounds futuristic, but it is already becoming real with glasses that can see what you see, understand context, and respond in real time. Here’s why that matters…
-
AI chatbot teaches AI student to love owls despite data removal
By
–
#AI #Chatbot teaches AI 'student' to love owls, even after #Data is scrubbed
by Anthropic @TechXplore_com Learn more: https://
bit.ly/4tNNNj4 #ArtificialIntelligence #MachineLearning #ML #DL