Last year, I faced a critical decision: fine-tune our LLM or implement RAG? We chose fine-tuning. It was expensive, time-consuming, and didn’t solve our core problem. After building 20+ LLM applications, I’ve learned when to use each approach. Here’s the comprehensive decision framework that will save you months of work. Figure 1: Fine-Tuning vs RAG […]
Read more →Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
CrewAI: Building Collaborative Multi-Agent Systems with Role-Playing AI Agents
Introduction: CrewAI has emerged as one of the most intuitive frameworks for building multi-agent AI systems. Unlike traditional agent frameworks that focus on single-agent loops, CrewAI introduces a role-playing paradigm where specialized AI agents collaborate as a “crew” to accomplish complex tasks. Released in late 2023 and rapidly gaining adoption throughout 2024, CrewAI simplifies the […]
Read more →Prompt Injection Defense: A Complete Guide to Sanitization, Detection, and Output Validation
Prompt injection represents one of the most critical security vulnerabilities in LLM applications. As organizations deploy AI systems that process user inputs, understanding and defending against these attacks becomes essential for building secure, production-ready applications. Understanding Prompt Injection Attacks Prompt injection occurs when an attacker crafts malicious input that manipulates the LLM into ignoring its […]
Read more →Azure Event Hubs: A Solutions Architect’s Guide to Real-Time Data Streaming
Real-time data streaming has become essential for modern enterprises that need to process millions of events per second while maintaining low latency and high reliability. Azure Event Hubs stands as Microsoft’s fully managed, big data streaming platform, designed to handle massive throughput scenarios that traditional messaging systems simply cannot address. Having architected numerous streaming solutions […]
Read more →Batch Inference Optimization: Maximizing Throughput and Minimizing Costs
Introduction: Batch inference optimization is critical for cost-effective LLM deployment at scale. Processing requests individually wastes GPU resources—the model loads weights once but processes only a single sequence. Batching multiple requests together amortizes this overhead, dramatically improving throughput and reducing per-request costs. This guide covers the techniques that make batch inference efficient: dynamic batching strategies, […]
Read more →GitOps with a comparison between Flux and ArgoCD and which one is better for use in Azure AKS
GitOps has emerged as a powerful paradigm for managing Kubernetes clusters and deploying applications. Two popular tools for implementing GitOps in Kubernetes are Flux and ArgoCD. Both tools have similar functionalities, but they differ in terms of their architecture, ease of use, and integration with cloud platforms like Azure AKS. In this blog, we will […]
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