Learn about the obstacles faced by data scientists in LLM evaluation and discover effective strategies for overcoming them.

What is AI data development? AI data development includes any action taken to convert raw information into a format useful to AI.

Learn how Snorkel, Databricks, and AWS enabled the team to build and deploy small, specialized, and highly accurate models which met their AI production requirements and strategic goals.

“Task Me Anything” empowers data scientists to generate bespoke benchmarks to assess and choose the right multimodal model for their needs.

Introducing Alfred: an open-source tool for combining foundation models with weak supervision for faster development of academic data sets.

This release features new GenAI tools and Multi-Schema Annotation, as well as new enterprise security tools and an updated home page.

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

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.

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

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

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

Vision language models demonstrate impressive image classification capabilities, but LLMs can help improve their performance. Learn how.

Fine-tuning specialized LLMs demands a lot of time and cost We developed Bonito to make this process faster, cheaper, and easier.

The manufacturing industry has experienced a massive influx of data. Snorkel AI and AWS Sage Maker can make that data actionable.

Snorkel’s Paroma Varma and Google’s Ali Arsenjani discus the role of data in the development and implementation of LLMs.