Category: Artificial Intelligence(AI)

Introduction: Not all queries are equal—some need fast, cheap responses while others require deep reasoning. Query routing intelligently directs requests to the right model, index, or processing pipeline based on query characteristics. Route simple factual questions to smaller models, complex reasoning to GPT-4, and domain-specific queries to specialized indexes. This approach optimizes both cost and […]

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 […]

Introduction: Conversation state management is the foundation of building coherent, context-aware AI assistants. Without proper state management, every message is processed in isolation—the assistant forgets what was discussed moments ago, loses track of user preferences, and fails to maintain the thread of complex multi-turn conversations. Effective state management involves storing conversation history, extracting and persisting […]

Introduction: Query understanding is the critical first step in building intelligent AI systems that respond appropriately to user requests. Before your system can retrieve relevant documents, call the right tools, or generate helpful responses, it needs to understand what the user actually wants. This involves intent classification (is this a question, command, or conversation?), entity […]