Modern AI Techniques & Integration

[YounesBensafia]

Files to create and modify

Create:

• docs/foundation_models.md: Summarize foundation models, fine-tuning techniques, instruction tuning, embeddings vs full LLMs
• docs/rag_systems.md: Summarize retrieval-augmented generation, vector DBs, pipelines, re-ranking, RAG vs fine-tuning, latency/memory considerations
• docs/multimodal_pipelines.md: Summarize vision-language, OCR+LLM, audio+text systems
• docs/diffusion_generative.md: Summarize diffusion and generative models, conditioning, safety filtering, and use cases
• docs/agents_orchestration.md: Summarize agent design, tool calling, workflows, failure recovery, real-world integration
• docs/api_vs_build.md: Document trade-offs between building models and using APIs, including cost, latency, privacy, and model selection

Acceptance Criteria

• Foundation model strategies and fine-tuning techniques are clearly documented
• RAG system design, pipelines, and trade-offs are summarized
• Multimodal pipelines and hybrid systems are described
• Diffusion/generative model applications, conditioning, and safety are covered
• Agents and orchestration workflows are detailed
• Guidance on building vs using APIs is clear, including trade-offs and example scenarios