Discover the latest enterprise readiness features for Snorkel Flow. Configure safeguards for data compliance and security.
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.
Retrieval-augmented generation (RAG) enables LLMs to produce more accurate responses by finding and injecting relevant context. Learn how.
How one large financial institution used call center AI to inform customer experience management with real-time data.
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.
