Intro to AI and Prompt Engineering Overview of AI and its applications Generative AI and Its Function

Generative AI and Its Function

Generative AI is a broader, more powerful AI approach designed not only to predict text but to create entirely new content—from text to images, music, and even code. It functions using advanced neural networks, specifically types like Transformer models (e.g., GPT, BERT), which allow it to handle vast amounts of data and generate nuanced outputs. Here’s how it works:

Training Phase
Generative AI is trained on large datasets of whatever it aims to generate (like text or images). During training, it learns patterns, context, and how pieces of data relate to one another. For text, it could learn grammar, syntax, and common language usage.
Encoding and Decoding
Most Generative AI models use encoding and decoding steps. The encoder understands input data by breaking down its meaning and context, while the decoder generates coherent output based on that understanding.
Fine-Tuning and Context
The AI can be fine-tuned on specific data (like medical text or legal documents) to specialize in a given area. It processes input prompts (like questions or incomplete text) to understand context and generate relevant, on-point answers.
Application
Generative AI powers tools like ChatGPT, Midjourney, and DALL-E, producing everything from conversational text to unique visuals by recombining learned patterns in unique, creative ways.

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