Title: ETH_Sem6 / DC / W11_GenerativeAI

Q: What is a generative model?
A: A model which produces new data of a certain type, some popular models:
- ChatGPT for text
- DALLE3, Stable Diffusion or Midjourney for images
- Voice Engine for audio

Q: REINVENT4 Generators
A: Generative model for molecules:

Q: SELFIES
A: SELF-referencIng Embedded String
Alternative to SMILES that is semantically robust, so all SELFIES are valid molecules

Q: STONED
A: Superfast Traversal, Optimization, Novelty, Exploration and Discovery: Can be used with SELFIES in classical generative AI for making new molecules:
- Local exploration by mutation of SELFIES characters
- Global exploitation by interpolating between two SELFIES

Genetic algorithms scheme

Q: Deep generative models
A: Generate data with the desired properties from (usually uniform or normal) noise.

Q: Generative adversarial networks (GANs)
A: Image (or whatever) generated from noise and classified as real or fake by discriminator. The generator tries to trick the discriminator while the discriminator tries to unmask the generator.

Q: Diffusion models
A: Generating content (images, molecules etc.) from noise
Molecules can be denoised starting from random coordinates by (advanced models) taking account for rotations/translations