- Generative AI - Home
- Generative AI Basics
- Generative AI Basics
- Generative AI Evolution
- ML and Generative AI
- Generative AI Models
- Discriminative vs Generative Models
- Types of Gen AI Models
- Probability Distribution
- Probability Density Functions
- Maximum Likelihood Estimation
- Generative AI Networks
- How GANs Work?
- GAN - Architecture
- Conditional GANs
- StyleGAN and CycleGAN
- Training a GAN
- GAN Applications
- Generative AI Transformer
- Transformers in Gen AI
- Architecture of Transformers in Gen AI
- Input Embeddings in Transformers
- Multi-Head Attention
- Positional Encoding
- Feed Forward Neural Network
- Residual Connections in Transformers
- Generative AI Autoencoders
- Autoencoders in Gen AI
- Autoencoders Types and Applications
- Implement Autoencoders Using Python
- Variational Autoencoders
- Generative AI and ChatGPT
- A Generative AI Model
- Generative AI Miscellaneous
- Gen AI for Manufacturing
- Gen AI for Developers
- Gen AI for Cybersecurity
- Gen AI for Software Testing
- Gen AI for Marketing
- Gen AI for Educators
- Gen AI for Healthcare
- Gen AI for Students
- Gen AI for Industry
- Gen AI for Movies
- Gen AI for Music
- Gen AI for Cooking
- Gen AI for Media
- Gen AI for Communications
- Gen AI for Photography
Discuss Generative AI
Generative AI is a type of artificial intelligence technology that generates new text, audio, video, or any other type of content by using algorithms like Generative Adversarial Networks or Variational Auto Encoders (VAEs). It learns patterns from existing training data and produces new and unique output that resembles real-world data.
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