GenAI Evaluation & LLM Benchmarking for Production #genai #generativeai #aigenerated

Description

How do you evaluate a Generative AI application in production? In this SmartSkale video, we explain GenAI evaluation and LLM benchmarking frameworks used in real-world AI systems. You’ll learn how to measure Large Language Model (LLM) performance using automated metrics, human evaluation, hallucination detection techniques, regression testing, and domain-specific benchmarks. We also cover how to design a continuous evaluation pipeline to monitor model quality, detect performance drift, and ensure safe deployment in enterprise environments. This video is ideal for Machine Learning engineers, AI developers, MLOps professionals, and interview candidates preparing for system design rounds. Understanding LLM evaluation frameworks is critical when deploying RAG systems, fine-tuned models, and production-grade GenAI applications. Key topics covered: Automated LLM evaluation metrics Human-in-the-loop validation Hallucination detection strategies Regression testing for prompt and model updates Domain-specific AI benchmarks Continuous evaluation pipelines (LLMOps) Subscribe to SmartSkale for practical, production-focused AI and ML content. #genai #LLMEvaluation #LLMBenchmarking #artificialintelligence #MachineLearning #mlops #llmops #generativeai #RAG #promptengineering #aiengineering #deeplearning #aiproduction #ModelMonitoring #smartskale #aigenerated