Generative AI

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Generative AI is a type of artificial intelligence that creates new content, such as text, images, and code, by learning patterns from vast datasets. Unlike traditional AI, which is often rule-based, generative AI extrapolates from its training data to produce original outputs in response to prompts. Examples include generating a story from a text prompt, creating realistic images from a description, or composing music.  

How it works

Shape

Training

Generative AI models are trained on massive amounts of existing data, such as text, images, or audio.

Pattern recognition

During training, the model learns the underlying patterns, structures, and relationships within the data.

Content generation

When given a prompt, the model uses its learned patterns to generate new content that is similar to its training data but is not a direct copy. For example, a model trained on thousands of images of sneakers can create a new, unique image of sneakers with a "goat charm" because it understands the features of both sneakers and charms.

Generative-AI

Key applications

  • Content creation: Generating blog posts, stories, and articles. 

  Art and design: Creating unique images, designs, and videos based on text descriptions. 

  Coding: Assisting developers by generating lines of code or writing entire programs. 

  Communication: Powering advanced chatbots and virtual assistants that can produce human-like responses. 

  Research: Helping to analyze data and generate synthetic data for training other AI models. 

  • Generative AI Explained In 5 Minutes | What Is GenAI? – YouTube

Advanced Executive Program In Applied Generative AI – https://www.simplilear… In this video on Introduction t…

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