Overview

This book offers a practical, end-to-end guide to Generative AI System Design, blending core concepts with real-world applications. Key topics include: GenAI & ML Foundations: Neural networks, transformers, attention mechanisms, and tokenization. Model Efficiency: Techniques like parallelism, quantization, pruning, and knowledge distillation. Core Components: Embeddings, scene graph generation, text-to-phoneme conversion, and more. Design Framework: A structured 7-step approach for building scalable GenAI systems. System Blueprints: Detailed system design for Text-to-Text, Text-to-Speech, Text-to-Image, and Text-to-Video generation. Tech Stack: Overview of GenAI frameworks, infrastructure, and tools. Interview Prep: Tips, resources, and AI-driven evaluation for system design interviews. Future Trends: Responsible AI, GenAI for low-power devices, and next-gen models. Case Studies: Real-world GenAI application

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