Fundamentals of Cost-Efficient AI
Academic Press Inc (Verlag)
978-0-443-33362-0 (ISBN)
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The book covers fine-tuning and compression techniques such as low-rank adaptation (LoRA), parameter-efficient fine-tuning (PEFT), adapter-based tuning, pruning, and quantization. It also explores inference acceleration through Flash Attention, prefill optimization, and speculative decoding, and explains how mixture-of-experts (MoE) architectures can scale models efficiently across GPUs and edge devices.
To build a strong conceptual understanding, the text introduces fundamentals of GPU architecture, matrix multiplication, memory hierarchies, and parallelization strategies, helping readers develop an intuition for optimizing training and inference pipelines.
While applicable across domains, the book places special emphasis on healthcare and biomedicine, where efficient AI can reduce costs and improve diagnostics, precision medicine, and clinical decision support. Real-world case studies and interviews with experts from organizations such as Google and Microsoft provide practical insights into building scalable healthcare AI systems. Aimed at graduate students, researchers, clinicians, biomedical engineers, data scientists, and AI practitioners, this book bridges algorithmic principles with applied implementation.
Rohit Kumar is a highly accomplished executive with many years of experience in the US Silicon Valley tech industry, specializing in innovative applications of AI and machine learning within the domains of healthcare and biomedicine. As a first-generation serial entrepreneur and investor in multiple successful startups, Rohit's contributions have left an indelible mark on the intersection of technology and healthcare. Currently, Rohit serves as the CTO of SublimeAI, a US-based AI company that has made significant strides in revolutionizing healthcare through AI-driven solutions. In this role, he spearheads the development of cutting-edge AI technologies aimed at improving patient care, diagnostics, and medical research. Additionally, Rohit heads R&D for CSC - an initiative of the Ministry of Electronics and IT (MeitY), Government of India, with a primary focus on harnessing AI to address critical healthcare challenges in the Indian context
1. Introduction to Efficient AI Computing in Healthcare
2. Fundamentals of AI Model Efficiency in Biomedicine
3. Model Compression Techniques for Medical Data
4. Distributed Training and Parallelism in Healthcare AI
5. Gradient Compression for Efficient Medical Training
6. On-Device Optimization for Medical Devices
7. Application-Specific Efficiency in Biomedicine
8. Quantum Machine Learning and Efficiency in Biomedicine
9. Performance Optimization with PyTorch in Healthcare AI
10. Advances in Model Efficiency for Biomedicine
11. Mixture of Experts Models in Healthcare AI
12. Managing Resource Constraints in Medical AI
13. Interviews with Industry Leaders in Healthcare AI
14. Future Trends and Challenges in Healthcare AI
| Erscheint lt. Verlag | 1.5.2026 |
|---|---|
| Verlagsort | San Diego |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 450 g |
| Themenwelt | Medizin / Pharmazie ► Gesundheitswesen |
| Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie | |
| Naturwissenschaften ► Biologie | |
| Technik ► Medizintechnik | |
| ISBN-10 | 0-443-33362-9 / 0443333629 |
| ISBN-13 | 978-0-443-33362-0 / 9780443333620 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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