Large language models (LLMs) are deep learning models trained on massive amounts of text and equipped with tens of billions or even trillions of parameters.

Generative artificial intelligence is a technology that can automatically create content such as text, images, audio, video, and code.

Deep learning (DL) is a core technology of artificial intelligence. It uses multi-layer neural networks to automatically learn features and recognize patterns from massive amounts of data.

Machine Learning (ML) is a core branch of artificial intelligence (AI) that enables systems to automatically learn patterns from data and use them to make predictions or decisions.

Prompt engineering is the systematic designing, optimizing, and managing of prompts to guide generative AI models toward producing high-quality, expected results.

Reinforcement Learning from Human Feedback (RLHF) is an optimization technique that incorporates human preference data into the training of artificial intelligence models.

Machine Learning Operations (MLOps) is an engineering framework that standardizes the development, deployment, and O&M of machine learning models.

Skills are capability encapsulation mechanisms that organize professional knowledge, such as coding experience and solutions to common problems, into reusable modules.