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