By MICHAEL CIRCLE
The Data Group News Service
Databricks, the data and AI company, announced an expanded collaboration with NVIDIA on Monday to optimize data and AI workloads by bringing NVIDIA's CUDA accelerated computing to the core of Databricks' data intelligence platform.
As data preparation, curation and processing are essential for using enterprise data in generative AI applications, the partnership aims to boost the efficiency, accuracy and performance of AI development pipelines.
Databricks plans to add native support for NVIDIA GPU acceleration on its platform. This builds on the companies' existing work to offer enhanced experiences for enterprises training machine learning models, building generative AI applications or optimizing digital twins.
"We're excited to help every organization build their own AI factories on their own private data," said Ali Ghodsi, co-founder and CEO at Databricks.
Databricks will develop native support for NVIDIA-accelerated computing in its next-generation Photon query engine to improve speed and efficiency for data warehousing and analytics workloads. The companies believe this will lead to new levels of price-performance.
At the recent COMPUTEX event, Databricks' open source model DBRX became available as an NVIDIA NIM microservice for easy deployment of generative AI models in applications.
"Reducing data processing energy demands with accelerated computing is essential to sustainable AI platforms," said NVIDIA founder and CEO Jensen Huang.
The announcement follows Databricks' recent acquisition of data management startup Tabular and its doubling down on the open Delta Sharing ecosystem.
Driven by surging demand for data and AI capabilities, Databricks reached over $1.6 billion in revenue for its fiscal year ending January 31, 2024, growing over 50% year-over-year.
For more on Databricks and Nvidia’s partnership, please visit Databricks and NVIDIA Strengthen Partnership to Accelerate Enterprise Data for the Era of Generative AI - Databricks.
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