Generative AI is more than just ChatGPT!

Here are some popular types of generative AI architectures:

1. Large Language Models (LLMs): Models designed for natural language understanding and generation. Examples: GPT, BERT
2. Variational Autoencoders (VAEs): Models that encode data into a latent space and decode it back, often used for generating new data. Examples: VQ-VAE, Beta-VAE
3. Generative Adversarial Networks (GANs): Models consisting of a generator and a discriminator that compete to produce realistic data. Examples: StyleGAN, BigGAN
4. Diffusion Models: Models that generate data by reversing a diffusion process. Examples: DALL-E 2, Imagen
5. Autoregressive Models: Models that generate data one step at a time, based on previous steps. Examples: WaveNet, PixelCNN
6. Multimodal Models: Models that handle and generate multiple types of data, such as text and images. Examples: CLIP, DALL-E
7. Specialized Models: Models designed for specific tasks or optimizations. Examples: DeepDream, Reformer