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Source channel @githubtrending · Post #14693 · May 10
#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai
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@libreware · Post #1185 · 09/26/2023, 11:04 PM
Meshenger is a P2P Android phone app that started out as a demo for community mesh networks. Meshenger started out as an idea to promote off the grid mesh networks and has now reached its initial goal. In this talk I will talk about the idea behind it, the story how it came to be and of course how it works. https://media.ccc.de/v/camp2023-57107-meshenger #P2P#Meshenger#Mesh#MeshNetwork#ChaosComputerClubBerlin #CCCde