Breaking down Microsoft code and products and helping you make sense of it.
The article discusses Microsoft’s AI development tools, highlighting alternatives to Open Source solutions like LangChain. It covers Semantic Kernel and Azure AI SDK for application building, Prompt Flow and Responsible AI tools for evaluation and debugging, Azure AI Studio for no-code workflows, and Semantic Kernel Planners for complex applications. Microsoft offers secure, scalable solutions.
AI technology is evolving rapidly, with open-source frameworks like LangChain, LangSmith, LangFlow, and LangGraph supporting developers. LangChain facilitates application building with LLMs, LangSmith focuses on debugging, LangFlow offers a no-code design approach, and LangGraph enhances control for complex workflows. Choosing the right tool depends on specific project needs.
Enterprises seeking to integrate AI can choose from three architectures: GPTs with prompt engineering for simple applications, Retrieval-Augmented Generation (RAG) for domain-specific queries leveraging internal data, and fine-tuning models for advanced customization. Each option caters to different AI maturity levels, enabling organizations to optimize AI usage efficiently and effectively.
Enterprises are increasingly adopting AI-driven chatbots to enhance efficiency and employee support, particularly using Retrieval-Augmented Generation (RAG) for accurate HR information. Copilot Studio simplifies chatbot creation, leveraging internal SharePoint data to provide precise answers while ensuring data security and scalability, ultimately improving employee satisfaction and streamlining HR processes.
The Real AI Bottleneck: Your Messy SharePoint By now we all know – AI is here, and it’s reshaping industries. … More
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