Introduction: Fine-tuning transforms general-purpose LLMs into specialized models that excel at your specific tasks. While prompting can get you far, fine-tuning unlocks capabilities that prompting alone cannot achieve: consistent output formats, domain-specific knowledge, reduced latency from shorter prompts, and behavior that would require extensive few-shot examples. This guide covers the practical aspects of LLM fine-tuning: […]
Read more →Month: February 2025
LLM Testing and Evaluation: Building Confidence in AI Applications
Introduction: LLM applications are notoriously hard to test. Outputs are non-deterministic, “correct” is often subjective, and traditional unit tests don’t apply. Yet shipping untested LLM features is risky—prompt changes can break functionality, model updates can degrade quality, and edge cases can embarrass your product. This guide covers practical testing strategies: building evaluation datasets, implementing automated […]
Read more →Private Kubernetes cluster in AKS with Azure Private Link
Today, we’ll take a look at a new feature in AKS called Azure Private Link, which allows you to connect to AKS securely and privately over the Microsoft Azure backbone network. In the past, connecting to AKS from an on-premises network or other virtual network required using a public IP address, which posed potential security […]
Read more →Building GDPR-Compliant FHIR APIs: A European Healthcare Guide
Executive Summary Building FHIR REST APIs in the European Union requires strict compliance with GDPR Article 9 for processing health data (special category personal data). This comprehensive guide provides solution architects and developers with production-ready patterns for implementing GDPR-compliant FHIR APIs, covering encryption, consent management, access controls, audit logging, and data subject rights. 🏥 HEALTHCARE […]
Read more →LLM Inference Optimization: KV Cache, Quantization, and Speculative Decoding (Part 2 of 2)
Introduction: LLM inference optimization is the art of making models respond faster while using fewer resources. As LLMs grow larger and usage scales, the difference between naive and optimized inference can mean 10x cost reduction and sub-second latencies instead of multi-second waits. This guide covers the techniques that matter most: KV cache optimization to avoid […]
Read more →Azure Synapse Analytics: A Solutions Architect’s Guide to Unified Data Analytics
The modern enterprise data landscape demands more than traditional data warehousing or isolated analytics solutions. Organizations need unified platforms that can handle everything from batch ETL processing to real-time streaming analytics, from structured data warehousing to exploratory data science workloads. Azure Synapse Analytics represents Microsoft’s answer to this challenge—a comprehensive analytics service that brings together […]
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