Databricks, a venture-backed by Andreessen Horowitz, NEA and Battery Ventures, released preliminary results of its AI research study, indicating AI is a challenge for most enterprises. 96 percent of responding organizations saw their challenges as data-related, when moving AI projects to production.
Serving as a leader in unified analytics emerging from their origin as creators of Apache Spark™, Databricks tackled the structural hurdle of data and AI residing in technology and organizational silos through the launch of its Unified Analytics Platform.
At the annual Spark + AI Summit held this past week in San Francisco Databricks unveiled new capabilities to lower the barrier for enterprises to innovate with AI via:
- MLflow: improves efficiency and effectiveness of machine learning with end-to-end workflow,
- Databricks Runtime for ML: simplifies and enables distributed deep learning; and
- Databricks Delta: simplifies data engineering by providing data reliability and performance at scale.
Ali Ghodsi, co-founder and CEO at Databricks, explained the import of their platform to users, saying, “Both organizational and technology silos create friction and slow down projects, becoming an impediment to the highly iterative nature of AI projects. Unified Analytics is the way to increase collaboration between data engineers and data scientists and unify data processing and AI technologies.”
