AKS workload identity and AKS pod managed identity both provide a way to manage access to Azure resources from within a Kubernetes cluster. However, there are some key differences between the two features. Scope AKS pod managed identity provides a managed identity for each individual pod within a Kubernetes cluster. This allows you to grant […]
Read more →Search Results for: name
LLM Memory Systems: Building Contextually Aware AI Applications
Introduction: Memory is what transforms a stateless LLM into a contextually aware assistant. Without memory, every interaction starts from scratch—the model has no knowledge of previous conversations, user preferences, or accumulated context. This guide covers the memory architectures that enable persistent, intelligent AI systems: conversation buffers for recent context, summary memory for long conversations, vector-based […]
Read more →MLOps Best Practices: Building Production Machine Learning Pipelines That Scale
Master MLOps practices for production machine learning systems. Learn data versioning, experiment tracking with MLflow, CI/CD for ML, model registry governance, and monitoring strategies for AWS, Azure, and GCP.
Read more →Advanced LoRA Techniques: Multi-LoRA, LoRA+, and Beyond
Last year, I fine-tuned a 7B parameter model with standard LoRA. It worked, but accuracy was 5% lower than full fine-tuning. After experimenting with Multi-LoRA, LoRA+, and advanced techniques, I’ve achieved 98% of full fine-tuning performance with 1% of the parameters. Here’s everything you need to know about advanced LoRA techniques. Figure 1: LoRA Techniques […]
Read more →EMR Modernization: Migrating from Legacy HL7 v2 to FHIR
Executive Summary Migrating from HL7 v2 to FHIR is one of the most critical modernization challenges facing healthcare IT. With billions of HL7 v2 messages processed daily across hospital EMRs, the transition requires careful planning using proven patterns like Strangler Fig, FHIR Facade, and Dual-Write strategies. 🏥 HEALTHCARE INTEROPERABILITY SERIES This article is part of […]
Read more →Tool Use and Function Calling: Extending LLM Capabilities with External Actions
Introduction: Function calling transforms LLMs from text generators into action-taking agents. Instead of just producing text responses, models can now decide when to call external functions, APIs, or tools to accomplish tasks. This capability enables building assistants that can search the web, query databases, send emails, execute code, and interact with any system that exposes […]
Read more →