Alex Merced's Data, Dev and AI Blog

Topic

AI

20 posts tagged “AI”.

  1. 31 min read

    The Filters We Build: Scams, Slop, and the Search for Signal, From Radio Ads to AI

    My grandparents' generation learned to tune out the radio pitchman. My parents learned to mute the commercials and hang up on telemarketers. I was…

  2. 17 min read

    Iceberg Variant Type for AI JSON Data

    A single LLM response is not a single value. It carries the generated text, a reasoning trace, one or more tool calls with their arguments, source…

  3. 16 min read

    Mapping the Variant Type in Iceberg v3: Standardizing Semi-Structured AI JSON Payloads

    AI applications are messy data producers. They create prompts, completions, tool calls, retrieval traces, ranking signals, evaluation scores, safety…

  4. 20 min read

    What AI Is and Isnt: A Laypersons Guide to How LLMs Actually Work

    Welcome to "Catching Up with Using AI for All Levels," a five-part series designed to take you from confused observer to confident AI user. This…

  5. 20 min read

    Getting Started with AI for Free: Every Tool Google Gives You at No Cost

    Most people think you need to pay $20 or $200 a month to get value from AI. That is not true. If you have a Google account which is free and most…

  6. 20 min read

    ChatGPT and Claude: Which AI Service Should You Pay For

    Part 2 of this series covered the extensive free AI tools Google offers through your Gmail account. Now we step up to the paid tier. ChatGPT from…

  7. 20 min read

    A Tour of Specialized AI Tools: Music, Video, Images, and More

    The first three parts of this series covered general purpose AI assistants: the chatbots and writing tools that handle text based tasks. But AI in…

  8. 20 min read

    Going Advanced: Open Source Models, Hermes Agent, and Local AI

    This is the final installment of "Catching Up with Using AI for All Levels." Parts 1 through 4 covered the fundamentals, free tools, paid services,…

  9. 5 min read

    A Journey from AI to LLMs and MCP - 10 - Sampling and Prompts in MCP – Making Agent Workflows Smarter and Safer

    Sampling and Prompts in MCP – Making Agent Workflows Smarter and Safer

  10. 5 min read

    A Journey from AI to LLMs and MCP - 9 - Tools in MCP – Giving LLMs the Power to Act

    Tools in MCP – Giving LLMs the Power to Act

  11. 4 min read

    A Journey from AI to LLMs and MCP - 8 - Resources in MCP – Serving Relevant Data Securely to LLMs

    Resources in MCP – Serving Relevant Data Securely to LLMs

  12. 5 min read

    A Journey from AI to LLMs and MCP - 7 - Under the Hood – The Architecture of MCP and Its Core Components

    Under the Hood – The Architecture of MCP and Its Core Components

  13. 5 min read

    Journey from AI to LLMs and MCP - 6 - Enter the Model Context Protocol (MCP) – The Interoperability Layer for AI Agents

    Enter the Model Context Protocol (MCP) – The Interoperability Layer for AI Agents

  14. 8 min read

    A Journey from AI to LLMs and MCP - 5 - AI Agent Frameworks – Benefits and Limitations

    AI Agent Frameworks – Benefits and Limitations

  15. 5 min read

    A Journey from AI to LLMs and MCP - 4 - What Are AI Agents – And Why They're the Future of LLM Applications

    What Are AI Agents – And Why They're the Future of LLM Applications

  16. 5 min read

    A Journey from AI to LLMs and MCP - 3 - Boosting LLM Performance – Fine-Tuning, Prompt Engineering, and RAG

    Boosting LLM Performance – Fine-Tuning, Prompt Engineering, and RAG

  17. 5 min read

    A Journey from AI to LLMs and MCP - 2 - How LLMs Work – Embeddings, Vectors, and Context Windows

    How LLMs Work – Embeddings, Vectors, and Context Windows

  18. 4 min read

    A Journey from AI to LLMs and MCP - 1 - What Is AI and How It Evolved Into LLMs

    What Is AI and How It Evolved Into LLMs

  19. 15 min read

    Building a Basic MCP Server with Python

    The Basics of Building a Basic MCP Server

  20. 12 min read

    Crash Course on Developing AI Applications with LangChain

    A guide on building AI applications with LangChain, a framework for developing AI applications powered by Large Language Models (LLMs).

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