Gen ai (generative ai) is an artificial intelligence that creates original images ,text, and video with the help of patterns in already existing data. It generates human-like outputs in response to user prompts. The Difference between traditional Ai and gen Ai is that traditional Ai requires specific training for certain unique tasks whereas general Ai can adapt to various domains and generate content across different fields. 

Main Types of GEN (AI)

Generative adversarial network (GAN) 

GAN is a machine learning framework where the neural networks, generator and discriminator compete against each other to create data such as images from training datasets. key components are generator, discriminator and adversarial training. The major challenges are mode collapse and training instability.

Variational encoders (VAE)

A variational auto encoder is a deep learning model which learns to compress data into a structured space and then reconstructs it. key aspects of VAE’s are generative architecture, latentspace, probabilistic approach, loss function. Main application’s are anomaly detection, data compression, and image synthesis.

Autoregressive models

An autoregressive model is a machine learning technique that predicts future values in a sequence based on its own previous value. Key components are past values, stationarity, weighted linear functions,use cases. Autoregressive models are frequently used to predict financial performances.

Transformer- based models

It is a type of neural network architecture designed for processing data like images, text, speech in parallel rather than sequentially. They use self attention mechanism to weigh the importance of different input. The key features are selfattention, paralleization, encoder and decoder, tokenization.

Recurrent neural networks (RNN)

Recurrent neural network is a type of deep learning model that is designed to process data like images,text,speech by using internal memory to retain data from previous input. Key characteristics of RNN are sequential processing, hidden state, shared weights, training method. It is an unsupervised learning algorithm.

Reinforcement learning

Reinforcement learning is a machine learning technique where an agent learns to make optimal decisions by interacting with the environment using trial and error methods. An agent is a decision maker and the environment is a world where the agent interacts. The key characteristics of reinforcement learning is exploration vs exploitation and sequential decision making.

To sum up, By now, you should have a basic idea about Generative AI and its types with that we could understand the role it plays in creativity and how unique each type is . Generative ai plays its role well and in our day today life generative ai plays a major role , learning generative ai is one of the best thing in 2026. If you are interested to learn more about these concepts enroll the best Generative AI course in Chennai at FITA Academy.