Open-Source Multimodal Data Ingestion and Enrichment at Scale with Spark NLP 6

This webinar introduces the recently released Spark NLP 6.0, an Apache 2.0 licensed open-source Python library which enables you to analyze large amounts of multi-modal data for batch LLM inference or to prepare data for RAG & LLM solutions – privately, efficiently, and at no cost. The library can operate on a single machine or container, or scale natively on any Spark hardware without code changes. Spark NLP recently crossed 150M downloads and this new release adds supports 3 major new use cases:

• Support for ingesting and pre-processing PDF, Excel, PowerPoint, text and image files. Prepare, analyze, and ingest all files formats into a LLM / RAG solution using one unified pipeline.
• Visual language models! Multiple VLMs of different sizes & features are natively available as steps in processing pipelines, enabling you to extract facts and answers from images and visual PDF files.
• Extract structure, semantics, and metadata from unstructured and visual data in all file formats – using batch inference at scale.

Join to learn how to apply these new capabilities by walking through Python notebooks showcasing end-to-end scenarios.