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What is Generative AI?

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Generative AI is a technology that uses machine learning models to create new, unique content. Unlike traditional AI, which analyzes data, generative AI creates new data based on learned patterns.

What is Generative AI?

Generative AI is a subset of deep learning. It is based on neural networks, such as transformers (e.g., GPT) or diffusion models (for images), trained on vast amounts of data. Their goal is not just to classify information, but to generate new samples that are statistically similar to what they were trained on.

How does Generative AI work?

The process typically involves two stages: 1. **Training:** The model analyzes millions of texts, images, or other data, discovering patterns and relationships. 2. **Inference:** Upon receiving a prompt from a user, the model uses its knowledge to create new content that matches the prompt.

Use Cases

01Content Creation

Generating articles, blog posts, advertising copy, and scripts. This significantly speeds up the work of copywriters and marketers.

02Software Development

Writing code, creating tests, and finding bugs. Tools like GitHub Copilot help developers work more efficiently.

/ FAQ

Regular AI (e.g., classifiers) is tuned to analyze data (e.g., determining if there is a cat in a photo). Generative AI is tuned to create new data (e.g., drawing a new picture of a cat).

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What is Generative AI?
/ What is Generative AI?

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