Introduction: Knowledge distillation transfers the capabilities of large, expensive models into smaller, faster ones that can run efficiently in production. Instead of training a small model from scratch, distillation leverages the “dark knowledge” encoded in a teacher model’s soft probability distributions—information that hard labels alone cannot capture. This guide covers the techniques that make distillation […]
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Microsoft Visual Studio 2015 Update 3 – hotfix build – 14.0.25422.1 (KB3165756)
Microsoft has released a hot-fix for Visual Studio 2015 Update 3, to fix certain critical issues identified after the release of Update 3. Supported Version Visual Studio 2015 Update 3 File name VS14-KB3165756.exe Date published 07/12/2016 File size 2.4 MB This update applied to: Visual Studio Professional 2015 Visual Studio Enterprise 2015 Visual Studio Community […]
Read more →Semantic Caching Strategies: Reducing LLM Costs Through Intelligent Query Matching
Introduction: Semantic caching revolutionizes how we handle LLM requests by recognizing that similar questions deserve similar answers. Unlike traditional exact-match caching, semantic caching uses embeddings to find queries that are semantically equivalent, returning cached responses even when the wording differs. This can reduce LLM API costs by 30-70% while dramatically improving response latency for common […]
Read more →LLM Routing and Load Balancing: Optimizing Cost and Performance Across Model Fleets
Introduction: LLM routing and load balancing are critical for building cost-effective, reliable AI systems at scale. Not every query needs GPT-4—many can be handled by smaller, faster, cheaper models with equivalent quality. Intelligent routing analyzes incoming requests and directs them to the most appropriate model based on complexity, cost constraints, latency requirements, and current system […]
Read more →Retrieval Evaluation Metrics: Measuring What Matters in Search and RAG Systems
Introduction: Retrieval evaluation is the foundation of building effective RAG systems and search applications. Without proper metrics, you’re flying blind—unable to tell if your retrieval improvements actually help or hurt end-user experience. This guide covers the essential metrics for evaluating retrieval systems: precision and recall at various cutoffs, Mean Reciprocal Rank (MRR), Normalized Discounted Cumulative […]
Read more →Prompt Debugging Techniques: Systematic Approaches to Fixing LLM Failures
Introduction: Prompt debugging is an essential skill for building reliable LLM applications. When prompts fail—producing incorrect outputs, hallucinations, or inconsistent results—systematic debugging techniques help identify and fix the root cause. Unlike traditional software debugging where you can step through code, prompt debugging requires understanding how language models interpret instructions and where they commonly fail. This […]
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