Cloudera Integrates NVIDIA Microservices to Boost Enterprise Gen AI Adoption
Cloudera today announced a major expansion of its collaboration with NVIDIA to accelerate the deployment of generative AI applications. By integrating NVIDIA’s AI microservices into its Cloudera Data Platform (CDP), the company aims to help businesses quickly build and scale customised LLMs on their own data. The partnership will see Cloudera leverage NVIDIA AI Enterprise, which includes NVIDIA Inference Manager (NIM) microservices, to unlock insights from the over 25 exabytes of data secured in CDP. This wealth of enterprise information will feed into Cloudera Machine Learning, the company’s end-to-end AI workflow service, to power a new wave of generative AI innovation. “Enterprise data, combined with a comprehensive full-stack platform optimised for large language models, plays a critical role in advancing an organisation’s generative AI applications from pilot to production,” said Priyank Patel, Vice President of AI/ML Products at Cloudera. “Cloudera is integrating NVIDIA NIM and CUDA-X microservices to power Cloudera Machine Learning, helping customers turn AI hype into business reality.” Bridging the Gap Between Models and Data A key challenge in enterprise AI is connecting foundation models with relevant business data to generate accurate, contextual outputs. NVIDIA’s NIM and NeMo Retriever microservices aim to bridge that gap by enabling developers to link LLMs with structured and unstructured enterprise data, from text documents to images and visualisations. Cloudera Machine Learning will offer integrated NIM model-serving capabilities to boost inference performance and achieve fault tolerance, low latency, and auto-scaling across hybrid and multi-cloud environments. The addition of NeMo Retriever will simplify the development of retrieval-augmented generation (RAG) applications, which enhance the accuracy of generative AI by retrieving relevant data on the fly. “Enterprises are eager to leverage their massive volumes of data for generative AI to build custom copilots and productivity tools,” said Justin Boitano, Vice President of Enterprise Products at NVIDIA. “The integration of NVIDIA NIM microservices into the Cloudera Data Platform offers developers a way to more easily and flexibly deploy LLMs to drive business transformation.” Empowering the Enterprise By streamlining the path from data to generative AI deployment, Cloudera and NVIDIA aim to accelerate enterprise adoption of transformative applications like coding assistants, chatbots, document summarisers, and semantic search tools. The partnership builds on the companies’ previous collaboration to harness GPU acceleration through the integration of NVIDIA RAPIDS into CDP. Patel emphasised the business benefits of the expanded partnership, noting, “In addition to delivering powerful generative AI capabilities and performance to customers, the results of this integration will empower enterprises to make more accurate and timely decisions while also mitigating inaccuracies, hallucinations, and errors in predictions – all critical factors for navigating today’s data landscape.” Cloudera will showcase its new generative AI capabilities at NVIDIA GTC, running from March 18-21 in San Jose, California. As leading enterprises explore the potential of foundation models to revolutionise their operations, Cloudera and NVIDIA are betting their collaboration can position customers at the forefront of the emerging era of enterprise AI.
Cloudera ML integrates NIM model-serving for faster, fault-tolerant inference with low latency and auto-scaling in hybrid and multi-cloud setups.
Cloudera ML integrates NIM model-serving for faster, fault-tolerant inference with low latency and auto-scaling in hybrid and multi-cloud setups.
["cloudera", "NVIDIA"]
["copilots", "Rapids", "cloudera", "machine learning", "AI", "chatbots", "ML", "RAG", "Aim", "generative AI", "foundation models", "NVIDIA"]
["AI", "machine learning", "ML", "generative AI", "foundation models", "Aim", "Rapids", "RAG", "copilots", "chatbots"]
Shyam is a tech journalist with expertise in policy and politics, and exhibits a fervent interest in scrutinising the convergence of AI and analytics in society. In his leisure time, he indulges in anime binges and mountain hikes.