Last year, I deployed an AI model to a mobile device. The first attempt failed—the model was too large, inference was too slow, and battery drain was unacceptable. After optimizing 15+ models for edge deployment using ONNX Runtime, I’ve learned what works. Here’s the complete guide to running AI models on-device with ONNX Runtime. Figure […]
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RAG Optimization: Query Rewriting, Hybrid Search, and Re-ranking
Introduction: Retrieval-Augmented Generation (RAG) grounds LLM responses in factual data, but naive implementations often retrieve irrelevant content or miss important information. Optimizing RAG requires attention to every stage: query understanding, retrieval strategies, re-ranking, and context integration. This guide covers practical optimization techniques: query rewriting and expansion, hybrid search combining dense and sparse retrieval, re-ranking with […]
Read more →LLM Routing and Model Selection: Optimizing Cost and Quality in Production
Introduction: Not every query needs GPT-4. Routing simple questions to cheaper, faster models while reserving expensive models for complex tasks can cut costs by 70% or more without sacrificing quality. Smart LLM routing is the difference between a $10,000/month AI bill and a $3,000 one. This guide covers implementing intelligent model selection: classifying query complexity, […]
Read more →Designing Enterprise VPC Networks on Google Cloud: From Zero Trust to Global Scale
Enterprise VPC design on Google Cloud requires balancing security, performance, and operational simplicity. This comprehensive guide covers Zero Trust architecture, global network design, VPC Service Controls, and hybrid connectivity patterns that meet the demands of modern enterprise workloads. Zero Trust Network Architecture Zero Trust assumes no implicit trust—every access request must be authenticated and authorized […]
Read more →Cloud VM Showdown: Choosing Between GCP Compute Engine, AWS EC2, and Azure Virtual Machines
Introduction: Choosing the right virtual machine platform is one of the most consequential decisions in cloud architecture, directly impacting performance, cost, and operational complexity for years to come. This comprehensive comparison examines GCP Compute Engine, AWS EC2, and Azure Virtual Machines through the lens of enterprise requirements—evaluating compute options, pricing models, networking capabilities, and operational […]
Read more →Semantic Caching for LLM Applications: Cut Costs and Latency by 50%
Introduction: LLM API calls are expensive and slow. A single GPT-4 request can cost cents and take seconds—multiply that by thousands of users asking similar questions, and costs spiral quickly. Semantic caching solves this by recognizing that “What’s the weather in NYC?” and “Tell me NYC weather” are essentially the same query. Instead of exact […]
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