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Artificial Intelligence (AI):

Artificial Intelligence is any system that simulates human intelligence and skills.

AI is not confined to "thinking" like humans but encompasses many human-like capabilities, including learning, problem-solving, perception, and language understanding.

Examples: Self-driving cars and virtual assistants.

Machine Learning (ML):

Machine Learning is a specialized subset of AI centered around the concept that machines can learn from data, identify patterns, and make decisions with minimal human direction.

Examples: Systems for product recommendations and fraud detection.

Generative AI (GenAI):

AI systems that can generate new and original content that is similar to their training data, such as text, images, audio, and music.

Natural Language Processing (NLP):

NLP focuses on training AI to understand, interpret, and generate human language text or speech.

Large Language Models (LLMs):

LLM is a type of GenAI model specifically trained using massive amounts of text data for NLP tasks.

Prompt:

Prompts are inputs that guide the model in creating output.

System prompt - is the input used to provide initial context and instruction to the LLMs.

User prompt - is the input the user provides, often in the form of text messages sent to the LLMs.

Digital Equity:

Fair and inclusive access to technology, the internet, and digital skills ensures everyone can fully participate in society, regardless of socioeconomic, geographic, or demographic barriers.

AI Governance:

AI Governance involves the policies, guidelines, and practices established to oversee the ethical development, deployment, and use of artificial intelligence.