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Databricks introduces GPT-5.5 for enterprise agent workflows, achieving state-of-the-art on the OfficeQA Pro benchmark with a 46% error reduction over GPT-5.4.
An analysis of three new Postgres-compatible cloud databases—Snowflake Postgres, Databricks Lakebase, and Azure HorizonDB—highlighting their distinct architectures and the vendor lock-in implications for enterprise data platforms.
This article explains how Databricks' Lakebase architecture achieves a 5x improvement in Postgres write throughput by disabling Full Page Writes (FPW) and leveraging stateless compute with distributed storage.
This guide demonstrates how to configure ChatGPT as a data agent by integrating plugins to access data sources such as Databricks, Slack, and Google Drive, enabling teams to build and use a consolidated data context skill.
This article advises on improving ChatGPT's data analysis accuracy by grounding it in a semantic layer through data plugins, which can be built from scratch or integrated with existing systems like Snowflake Cortex and Databricks Genie, requiring sustained organizational commitment.
OpenAI partners with Databricks to release the GPT-5.5 model, achieving a 46% reduction in error rate in agent frameworks, becoming the only model to exceed 50% on benchmarks, with significant improvements in parsing quality and function calling capabilities.