There is a lot of enterprise data trapped in PDF documents. To be sure, gen AI tools have been able to ingest and analyze PDFs, but accuracy, time and cost have been less than ideal. New technology from Databricks could change that.The company this week detailed its "ai_parse_document" technology, now integrated with Databricks' Agent Bricks platform. The technology addresses a critical bottleneck in enterprise AI adoption: Approximately 80% of enterprise knowledge remains locked in PDFs, reports and diagrams that AI systems struggle to accurately process and understand."It's a common assumption that parsing PDFs is a solved problem, but in reality, it isn't," Erich Elsen, principal research scientist at Databricks, told VentureBeat. "The challenge i [...]
There is no shortage of AI benchmarks in the market today, with popular options like Humanity's Last Exam (HLE), ARC-AGI-2 and GDPval, among numerous others.AI agents excel at solving abstract ma [...]
Many enterprises running PostgreSQL databases for their applications face the same expensive reality. When they need to analyze that operational data or feed it to AI models, they build ETL (Extract, [...]
Data teams building AI agents keep running into the same failure mode. Questions that require joining structured data with unstructured content, sales figures alongside customer reviews or citation co [...]
A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]
Five years ago, Databricks coined the term 'data lakehouse' to describe a new type of data architecture that combines a data lake with a data warehouse. That term and data architecture are n [...]
Most enterprise RAG pipelines are optimized for one search behavior. They fail silently on the others. A model trained to synthesize cross-document reports handles constraint-driven entity search poor [...]
The intelligence of AI models isn't what's blocking enterprise deployments. It's the inability to define and measure quality in the first place.That's where AI judges are now playi [...]
Traditional ETL tools like dbt or Fivetran prepare data for reporting: structured analytics and dashboards with stable schemas. AI applications need something different: preparing messy, evolving oper [...]