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
We introduce a benchmark to evaluate the capability of AI to solve problems in theoretical physics, focusing on high-energy theory and cosmology. The first iteration of our benchmark consists of 57 problems of varying difficulty, from undergraduate to research level. These problems are novel in the sense that they do not come from public problem collections. We evaluate our data…
Learn how to evaluate GenAI systems, generate synthetic training data, and optimize retrieval with foundation models from Anthropic, Cohere, and Meta by taking advantage of native AWS Bedrock and SageMaker integration in Snorkel Flow.
Learn about large language model (LLM) alignment and how it maximizes the effectiveness of AI outputs for organizations.
Unlock GenAI projects with scalable data labeling tools, techniques, & best practices.
Discover the power of integrating Databricks and Snorkel Flow for efficient data ingestion, labeling, model development, and AI deployment.
In this webinar, we will explain how to operationalize prompt engineering as a component of the GenAI development process.
Discover how Snorkel AI’s methodical workflow can simplify the evaluation of LLM systems. Achieve better model performance in less time.
Accelerate LLM development with Snorkel Flow and SageMaker. Automate dataset curation, accelerate training, and gain a competitive advantage.
