A recent press release reports, “Despite the allure of artificial intelligence (AI), most enterprises are struggling to succeed with AI. Preliminary findings of a Databricks commissioned research study reveals that 96 percent of organizations say data-related challenges are the most common obstacle when moving AI projects to production. Data is the key to AI, but data and AI sit in technology and organizational silos. Databricks, the leader in unified analytics and founded by the original creators of Apache Spark™, addresses this AI dilemma with the Unified Analytics Platform… Databricks launched new capabilities to lower the barrier for enterprises to innovate with AI. These new capabilities unify data and AI teams and technologies: MLflow for developing an end-to-end machine learning workflow, Databricks Runtime for ML to simplify distributed machine learning; and Databricks Delta for data reliability and performance at scale.”
Ali Ghodsi, co-founder and CEO at Databricks, commented, “To derive value from AI, enterprises are dependent on their existing data and ability to iteratively do machine learning on massive data sets. Today’s data engineers and data scientists use numerous, disconnected tools to accomplish this, including a zoo of machine learning frameworks… 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.”
Read more at Business Wire.
Photo credit: Databricks