The essentials of evaluating LLM systems

Evaluating LLM systems has become a critical task for enterprises seeking to leverage artificial intelligence effectively. In this presentation, Snorkel AI's Rebekah Westerlind and Venkatesh Rao provide a comprehensive overview of the evaluation process, emphasizing the need for specialized, fine-grained, and actionable evaluations. The session begins with an introduction to the unique challenges of evaluating LLM systems, highlighting the absence of universal benchmarks or mathematical formulas. Westerlind and Rao then discuss the importance of tailoring evaluations to specific use cases and business objectives. They outline a structured workflow designed to facilitate the evaluation process. The presentation covers key components such as defining evaluation criteria, selecting appropriate evaluators, and creating reference prompts. Viewers learn how to implement heuristic-based and predictive models as evaluators, as well as how to utilize LLMs for more nuanced assessments. The discussion includes methods for slicing data to gain insights into specific performance metrics, which can help identify areas for improvement. The session concludes with a live demonstration of the evaluation workflow, illustrating how to integrate these concepts into practical applications. This session was one of several from SnorkelCon 2024, Snorkel AI's inaugural user conference in New York City. See more SnorkelCon talks here: https://www.youtube.com/playlist?list=PLZePYakcDhmhJG4BF4y2QBc3EaBbV3IKm Learn more about LLM evaluation here: https://snorkel.ai/llm-evaluation-primer/ Timestamps: 00:00 Introduction 00:06 Overview of LLM Evaluation 01:13 Key Messages 02:43 Specialized Evaluations 03:56 Evaluators in the Product 04:28 Fine-Grained Evaluations 07:07 Actionable Evaluations 08:57 Iterative Workflow 09:00 Product Demo Introduction 09:05 Workflow Steps 09:39 Step 1: Onboarding 10:40 Step 2: Running the Benchmark 11:42 Step 3: Refining the Benchmark 12:14 Iteration Loop with Ground Truth 13:49 Step 4: LLM System Development 14:51 Live Product Demo 15:19 Step 1: Onboarding in Action 18:43 Step 2: Evaluating the Model 24:00 Evaluation Report Overview 30:11 Ground Truth Integration 31:40 Step 4: Refining LLM System 35:12 CEO Summary 37:13 Conclusion #enterpriseai #llmevaluation #snorkelcon2024 #snorkelcon