Introduction: Long contexts contain valuable information, but they also contain noise, redundancy, and irrelevant details that consume tokens and dilute model attention. Context distillation extracts the essential information from lengthy documents, conversations, or retrieved passages, producing compact representations that preserve what matters while discarding what doesn’t. This technique is crucial for RAG systems processing multiple […]
Read more →Category: Technology Engineering
Technology Engineering
Query Routing: Intelligent Request Distribution for Cost-Efficient AI Systems
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 […]
Read more →Knowledge Distillation: Transferring Intelligence from Large to Small Models
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 […]
Read more →Conversation State Management: Building Context-Aware AI Assistants
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 […]
Read more →Query Understanding and Intent Detection: Building Smarter AI Interfaces
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 […]
Read more →Certified–Professional Scrum Master-I(PSM-I)
Before I joined UnitedHealth Group as a Consultant in Jul 2010, I didn’t even hear about of Agile or Scrum.I have been working in an Agile environment for last 3 years and it was really interesting experience to develop high value applications and products using Scrum. I worked on few projects during the tenure as […]
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