#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
⚡️ Advanced Camera Control is now available for #Gen3 Alpha Turbo. Choose both the direction and intensity of how you move through your scenes for even more intention in every shot
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⚡️ Camera controls have appeared in Runway #Gen3 alpha!
No official announcement yet, but it looks like they’re rolling it out gradually. 😍
Credits: Pierrick Chevallier
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"The Schnitzel Dilemma"
A short film about two colleagues planning their lunch date. Generated with runwayml #Gen3 new Act-One model 😍
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