AI/ML Terminologies

	Description	Examples
Generative AI (GenAI)	A broad category of AI models that can create new content such as text, images, music, code, etc. - All LLMs are GenAI, but not all GenAI are LLMs (some generate images, music, etc.).	ChatGPT (text), DALL·E (images), Sora (video), GitHub Copilot (code)
Large Language Model (LLM)	A type of Generative AI specifically trained on vast amounts of text to understand and generate human language. - Text-based tasks like summarization, translation, question answering, and code generation.	GPT-4, Claude, PaLM, LLaMA
AI Agents	Software entities that can autonomously perceive, decide, and act in an environment to achieve a goal.	A shopping assistant that books a trip end-to-end; Auto-GPT.
Agentic AI	A subset of AI focused on autonomous agents with long-term planning, memory, tool use, and goal pursuit.	OpenAI’s experiments with tool-using GPT agents; Cognosys, HyperGPT.
Multi-Agent Systems (MAS)	Systems where multiple AI agents interact with each other, possibly collaborating or competing to achieve goals.	Multi-agent simulations, decentralized trading bots, or AI-driven game environments.
Machine Learning	Extract data, make predictions and perform actions. Deep Learning is its subfield.
Natural Language Processing	Language transaction like english to chinese.
Quantization	Quantization enables machine learning models to use less memory and computing power for faster responses and reduce costs. However, it can make AI inference less precise.
Pre-training
Fine-tuning	Fine tuning is a technique used to improve the performance of a pre-trained AI model on a specific task.

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