Pre-trainingPre-training is the foundational stage of developing a machine learning model, particularly for Large Language Models (LLMs) and Computer Vision. In this phase, an AI model is exposed to a massive, unlabeled dataset (often trillions of words or images) to learn the underlying structure, grammar, logic, and "world knowledge" of the data. Read More
Probabilistic ModelA Probabilistic Model is a mathematical representation that incorporates random variables and probability distributions to predict the likelihood of various outcomes. Unlike traditional "if-then" logic, which is rigid and binary, probabilistic models embrace uncertainty Read More
Prompt EngineeringPrompt Engineering is the strategic process of designing, refining, and optimizing inputs (prompts) to guide Large Language Models (LLMs) toward generating the most accurate, relevant, and high-quality outputs possible. Rather than writing code to tell a computer how to calculate a result, prompt engineering uses natural language to tell a model what the desired outcome should be. Read More
PromptingPrompting is the process of providing specific inputs text, images, or code to an Artificial Intelligence model to elicit a desired response. It is the primary interface between human intent and machine execution. Read More
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