Generative AI

1. Concepts

1.1. Models

1.1.1. Foundation models

1.1.2. Large language models (LLM)

1.1.3. Diffusion models

1.1.4. Frontier models

1.2. RAG

1.3. Temperature

1.4. Tokens

1.5. Context Window

1.6. Embedings

1.7. Vectors

1.8. Agents

1.9. Hallucinations

1.10. Bias

1.11. Inference

1.12. Transformer

2. Prompt Engeneering

2.1. Zero-shot prompting

2.2. Few-shot prompting

2.3. Chain-of-thought

2.4. Generated knowledge

2.5. Least to most

2.6. Self-refine

2.7. Maieutic prompting

3. Models

3.1. OpenAI

3.1.1. GPT

3.1.2. o1

3.2. Microsoft

3.2.1. Phi3

3.3. Anthropic

3.3.1. Claude

3.4. Google

3.4.1. Gemini

3.5. Meta

3.5.1. Llama

3.6. Amazon

3.6.1. Titan

3.7. xAI

3.7.1. Grok

3.8. Other

3.8.1. Falcon

3.8.2. Mistral

4. Platforms

4.1. AzureAI

4.2. Amazon

4.3. Huggingface

5. Tools & Frameworks

5.1. LlamaIndex

5.2. Semantic Kernel

5.3. Autogen

5.4. Langchain

5.5. Haystack

5.6. Promptflow

5.7. Prompty

5.8. Vector DB

5.8.1. Qdrant

5.8.2. ChromaDB

5.8.3. Redis

5.8.4. Pinecone