Resource library
Evaluating Coding Agent Capabilities with Terminal-Bench: Snorkel’s Role in Building the Next Generation Benchmark
Closing the Evaluation Gap in Agentic AI
Announcing a $3M commitment to launch Open Benchmarks Grants
Benchtalks #1: Alex Shaw (Terminal-Bench, Harbor) – Building the Benchmark Factory
Building FinQA: An Open RL Environment for Financial Reasoning Agents
In this webinar, we’ll explain how to capture SME domain knowledge, and use it to automate and scale PDF classification and information extraction tasks. Specifically, we’ll demonstrate techniques such as candidate span generation, sequence tagging, and LLM prompting.
Learn about the obstacles faced by data scientists in LLM evaluation and discover effective strategies for overcoming them.
Snorkel AI and AWS are partnering to help enterprises build, deploy, and evaluate custom, production-ready AI models. Learn how.
What is AI data development? AI data development includes any action taken to convert raw information into a format useful to AI.
In this webinar, we’ll explain how enterprise AI/ML teams use Snorkel Flow’s evaluation framework to measure GenAI performance based on SME guidelines and feedback, identify areas of improvement and take corrective action to reach production accuracy requirements.
In this demo, learn how Snorkel AI powers efficient data labeling and management for LLM fine-tuning, natively integrating with Amazon Bedrock and SageMaker for seamless, end-to-end development of specialized models.
Discover highlights of Snorkel AI’s first annual SnorkelCon user conference. Explore Snorkel’s programmatic AI data development achievements.
Snorkel AI has made building production-ready, high-value enterprise AI applications faster and easier than ever. The 2024.R3 update to our Snorkel Flow AI data development platform streamlines data-centric workflows, from easier-than-ever generative AI evaluation to multi-schema annotation.
