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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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