Tags: Prompting

How to fine tune an AI model

There are numerous ways to optimize model performance.  Retrieval Augmented Generation (RAG) and Prompt Engineering are 2 relevant strategies, but also consider fine-tuning a model.  Fine-tuning influences the model with additional examples that reflect specific requirements.  These examples adjust the pretrained internal weights so that it produces responses consistent with patterns in the training data. […]

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Develop generative AI apps that use tools

Artificial Intelligence (AI) is more than OpenAI or Anthropic who have created some very awesome LLMs that can do amazing things, especially with Natural Language Processing (NLP).  AI can also extract information from documents, convert text-to-speech and speech-to-text, provide metadata and summaries of images and videos, of course AI Agents.  All of the AI capabilities […]

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Orchestrate a multi-agent solution using the Microsoft Agent Framework

The Microsoft Agent Framework is an open-sourced SDK which combines the Semantic Kernel and AutoGen into a single, highly innovative set of AI capabilities into a single library.  AI features like: Unified model connectivity and chat clients for OpenAI, Azure OpenAI, Anthropic, Ollama, and other leading LLM providers. Multi-agent orchestration, allowing specialized AI agents to […]

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Develop an AI agent with Microsoft Agent Framework

You may have noticed that in my previous articles I used Azure AI Projects client library for Python – version 2.5.0 library.  Those articles illustrate how to build AI Agents, MCP Tools, and infer instructions using an LLM. Integrate custom tools into an AI Agent Integrate MCP Tools with AI Agents – Remote MCP server […]

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