Searching for null0

SummaryIn this podcast, Kirk Byers and John Capobianco discuss the  impact of AI on network automation and engineering. They explore the significance of ChatGPT, the challenges of inference, and the concept of Retrieval-Augmented Generation (RAG). John shares insights on using LangChain for building AI applications, and the role of AI agents. The conversation emphasizes the importance of adapting to AI technologies and the potential for enhancing productivity in network engineering.TakeawaysChatGPT marked a significant turning point in AI awareness.Retrieval-Augmented Generation (RAG) enhances AI capabilities.LangChain simplifies the integration of AI with network tools.AI agents can automate complex tasks in network management.Fine-tuning models can improve AI performance in specific domains.AI can significantly reduce the time needed for project development.Chapters00:00 - Introduction to AI and Network Automation01:42 - The Impact of ChatGPT05:50 - Understanding Hallucinations and Inference09:53 - Retrieval-Augmented Generation (RAG) Explained14:42 - Building with LangChain18:37 - Exploring Models and Local LLMs22:55 - Exploring Fine-Tuning and RAG Techniques25:34 - Integrating AI with Network Data29:34 - The Rise of AI Agents34:28 - Modernizing Code39:53 - Future Directions for Network EngineersReference MaterialsSelector https://www.selector.ai/John Capobianco YouTube Video on "Multi Agent AI for Network Automation" https://www.youtube.com/watch?v=8GwSIRGae10LangChain https://www.langchain.com/LlamaIndex https://www.llamaindex.ai/Streamlit https://streamlit.io/