Key AI Concepts (1)#

To use AI effectively, it’s important to understand the key concepts behind it. This helps you understand how AI services and tools work, and why the latest news and trends matter.

AI is still evolving at a rapid pace. Services and tools are continuously updated, and new developments emerge all the time. If you build a solid foundation, you can follow the changes more easily and keep improving your ability to apply AI in practice.

Key AI Concepts (2)#

In this chapter, we cover key concepts you’ll frequently encounter when turning a pre-trained LLM into a real product: fine-tuning, RAG, function calling, and MCP.

Fine-tuning#

Fine-tuning is the process of further training a pre-trained model to better fit a specific purpose. Thanks to open-source culture, training datasets and pre-trained models are often publicly available, and you can fine-tune them to improve performance or specialize in a particular domain.

I Thought AWS Bedrock Was Just Relaying Models — Turns Out It Runs Them Directly#

It Started With a Small Question#

I knew that with AWS Bedrock you could call external LLMs (Large Language Models) like Claude or GPT. But the more I thought about it, the stranger it seemed. Claude is a model owned by Anthropic, and GPT is a model owned by OpenAI. These are another company’s core assets — so how on earth does AWS get to offer them inside its own service?