resources

Resource library

Explore our complete library of resources including blogs, benchmarks, research papers, and more.

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Blog

Data 2.0 and the research era of AI data

Announcing Snorkel’s $350M fundraise to build the frontier lab for AI data.

September 22, 2026
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Blog

Terminal-Bench 4.0: Why Continuous Benchmarks Require Continuous QA

Announcing a $3M commitment to launch Open Benchmarks Grants
August 28, 2026
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Blog

Grok 4.5 Testing Results: How SpaceXAI’s New Model Performs on Real Professional Work

Announcing a $3M commitment to launch Open Benchmarks Grants
July 8, 2026
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Blog

Why coding agents need better data, evals, and environments

Announcing a $3M commitment to launch Open Benchmarks Grants
May 11, 2026
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Blog

Closing the Evaluation Gap in Agentic AI

Announcing a $3M commitment to launch Open Benchmarks Grants

February 11, 2026
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Blog

Why Frontier Agents Fail Real Engineering Work: Two Terminal-Bench 3.0 Task Deep Dives

Announcing a $3M commitment to launch Open Benchmarks Grants
August 24, 2026
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Blog

Building FinQA: An Open RL Environment for Financial Reasoning Agents

Announcing a $3M commitment to launch Open Benchmarks Grants
March 30, 2026
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Blog

The science of rubric design

Announcing a $3M commitment to launch Open Benchmarks Grants
September 11, 2025
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Blog

Benchtalks #3: We taught AI everything except how to learn

Featuring Parth Asawa (Continual Learning Bench)

June 25, 2026
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Webinar
How to optimize RAG pipelines for domain- and enterprise-specific tasks

RAG is the first step in building LLM-powered AI applications for enterprise use cases.

Aug 01, 2024 •
Snorkel Team
Learn more about How to optimize RAG pipelines for domain- and enterprise-specific tasks
How data slices transform enterprise LLM evaluation
Blog
How data slices transform enterprise LLM evaluation

Enterprises must evaluate LLM performance for production deployment. Custom, automated eval + data slices present the best path to production.

Aug 01, 2024 •
Learn more about How data slices transform enterprise LLM evaluation
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Webinar
Combining structured and unstructured data to enhance RAG capabilities

In this webinar, presented by Snorkel and Numbers Station, we’ll explain how to elicit data-driven insights backed by domain-knowledge using a multi-agent architecture and a fine-tuned LLM and/or RAG pipeline.

Jul 31, 2024 •
Snorkel Team
Learn more about Combining structured and unstructured data to enhance RAG capabilities
Meta’s Llama 3.1 405B is the new Mr. Miyagi, now what?
Blog
Meta’s Llama 3.1 405B is the new Mr. Miyagi, now what?

Meta’s Llama 3.1 405B, rivals GPT-4o in benchmarks, offering powerful AI capabilities. Despite high costs, it can enhance LLM adoption through fine-tuning, distillation, and as an AI judge.

Jul 25, 2024 •
Learn more about Meta’s Llama 3.1 405B is the new Mr. Miyagi, now what?
Meta’s new Llama 3.1 models are here! Are you ready for it?
Blog
Meta’s new Llama 3.1 models are here! Are you ready for it?

Meta released Llama 3 405B today, signaling a new era of open source AI. The model is ready to use on Snorkel Flow.

Jul 23, 2024 •
Learn more about Meta’s new Llama 3.1 models are here! Are you ready for it?
Data-centric AI with Snorkel and MinIO
Blog
Data-centric AI with Snorkel and MinIO

High-performing AI systems require more than a well-designed model. They also require properly constructed training and testing data.

Learn more about Data-centric AI with Snorkel and MinIO
Weak supervision for non-categorical applications + superalignment
Blog
Weak supervision for non-categorical applications + superalignment

We need more labeled data than ever, so we have explored weak supervision for non-categorical applications—with notable results.

Jul 02, 2024 •
Learn more about Weak supervision for non-categorical applications + superalignment
How to evaluate LLM accuracy for domain-specific use cases
Webinar
How to evaluate LLM accuracy for domain-specific use cases

In this webinar, Vincent Chen, Product Director at Snorkel AI, will discuss the importance of LLM evaluation, highlight common challenges and approaches, explain core concepts such as slices and quality models, and demonstrate Snorkel AI’s approach to LLM evaluation.

Jun 28, 2024 •
Snorkel Team
Learn more about How to evaluate LLM accuracy for domain-specific use cases
Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm
Blog
Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm

To tackle generative AI use cases, Snorkel AI + AWS launched an accelerator program to address the biggest blocker: unstructured data.

Jun 27, 2024 •
Learn more about Snorkel AI signs strategic collaboration agreement with AWS to help enterprises cross the demo-to-production chasm
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