Generative AI vs. Traditional AI

Introduction

• Explore generative AI vs. traditional AI

1. Predictive AI Architecture

• Machine learning
• Supervised and unsupervised learning
• Artificial neural networks
• Data models

2. Generative AI Models

• Foundation models
• Large language models (LLMs)
• Small language models (SLMs)
• Image diffusion models
• Generative pre-trained transformer (GPT)

3. Generative AI Architecture

• Prompt engineering
• Generative adversarial networks (GANs)
• Self-supervised learning
• Variational autoencoder (VAE)
• Building a generative AI system

4. Improving Generative AI

• Inferencing
• Filling gaps
• Agents
• Context windows

5. Generative AI Legal and Ethical Issues

• Traceable decision-making
• Hallucination liability
• Copyright training
• Mass data collection and privacy
• The expertise death spiral

Conclusion

• Next steps for AI