AI Fundamentals
Core concepts in artificial intelligence, machine learning, and large language models.
7 terms
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Autonomous Agent
An AI system capable of independently completing multi-step tasks by planning, executing, and self-correcting without human prompting.
Context Window
The maximum amount of text (measured in tokens) that an LLM can process in a single request, including both input and output.
Fine-tuning
The process of training a pre-trained model on a smaller, task-specific dataset to adapt its behavior for a particular use case.
LLM (Large Language Model)
A neural network trained on massive text datasets to predict and generate human-like text, powering all modern AI coding tools.
Prompt Engineering
The practice of designing and refining instructions given to an AI model to produce accurate, relevant, and useful outputs.
RAG (Retrieval-Augmented Generation)
A technique that enhances LLM responses by retrieving relevant documents from an external knowledge base before generating output.
Tokenization
The process of converting text into smaller units called tokens that a language model can process and reason over.
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