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Hybrid Intelligence Engineering: Combining Small & Large Language Models to Build Secure, Scalable and Affordable AI Solutions for Cloud and Edge
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Publisher: Independently Published
Published: Oct 17 2025
Pages: 164
Weight: 0.87
Height: 0.35 Width: 8.50 Depth: 11.00
Language: English
Hybrid Intelligence Engineering: Combining Small and Large Language Models to Build Secure, Scalable, and Affordable AI Solutions for Cloud and Edge
- crafted for maximum engagement and visibility in the AI and technology categories: Build the future of AI-where small and large language models work together seamlessly across the cloud and edge. Hybrid Intelligence Engineering is your complete guide to creating next-generation AI systems that are faster, smarter, and more affordable. Learn how to combine lightweight edge models for instant local processing with powerful cloud-based LLMs for deep reasoning and decision-making. Through text-based flowcharts, tables, and hands-on projects, this book shows you exactly how to design, deploy, and optimize hybrid AI workflows that balance speed, security, and cost. From architecture blueprints to real-world case studies, you'll gain practical skills to engineer scalable and responsible AI solutions for any environment. You'll Learn How To: - Orchestrate small and large LLMs for hybrid performance - Secure distributed inference pipelines - Optimize latency, throughput, and cost - Deploy AI efficiently on both cloud and edge - Build hands-on projects using Python and FastAPI Perfect For:
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