Software development company Cloudera recently announced a strategic partnership with NVIDIA to accelerate the deployment of generative AI applications. The collaboration will involve integrating NVIDIA's AI microservices into the Cloudera Data Platform (CDP) and is designed to help enterprises more quickly build and scale custom large language models (LLMs) based on their data. This initiative will provide enterprises with more powerful tools and technologies to better utilize their data resources and accelerate the development and deployment process of AI applications. This collaboration will bring more opportunities to enterprises, helping them make more efficient data-driven decisions and drive business development. The cooperation between Cloudera and NVIDIA will provide enterprises with more choices and flexibility, and is expected to promote the widespread application of AI technology in various industries.
As part of this collaboration, Cloudera plans to leverage NVIDIA AI Enterprise technology, including NVIDIA Inference Manager (NIM) microservices, to uncover the power of more than 25 exabytes of data in CDPs insights. This valuable enterprise information will be imported into Cloudera's machine learning platform, an end-to-end AI workflow service provided by the company, designed to drive a new round of generative AI innovation.
Priyank Patel, vice president of AI/ML products at Cloudera, pointed out that a full-stack platform that combines enterprise data and is optimized for large-scale language models is essential for taking organizations’ generative AI applications from pilot to production. It's important. Cloudera is currently integrating NVIDIA NIM and CUDA-X microservices to drive its machine learning platform and help customers transform the potential of AI into business reality.
This collaboration highlights the strength of Cloudera and NVIDIA in technological innovation and also demonstrates the rapidly growing market demand for generative AI applications. By integrating the resources and technical advantages of both parties, we will jointly promote the practical application of AI in enterprises and provide enterprises with more efficient and intelligent solutions.
In addition, by leveraging the massive data in CDP and combining it with the powerful capabilities of the Cloudera machine learning platform, enterprises can dig deeper into the value of data and achieve more accurate decisions and more efficient operations. Business operations. This cooperation will bring a more intelligent and automated future to enterprises and promote the development and progress of the entire industry.
In connecting models and data, enterprise AI faces a key challenge, that is, how to connect the basic Models are connected with relevant business data to produce accurate, contextual output. NVIDIA’s NIM and NeMo Retriever microservices aim to bridge this gap by enabling developers to connect LLMs (Large Language Models) with structured and unstructured enterprise data ranging from text documents to images and visualizations.
Specifically, Cloudera Machine Learning will provide integrated NIM model serving capabilities to enhance inference performance and enable fault tolerance, low latency and automatic scaling in hybrid and multi-cloud environments. The addition of NeMo Retriever will simplify the development of Retrieval Augmented Generation (RAG) applications, which improve the accuracy of generative AI by retrieving relevant data in real time.
Among them, NVIDIA NeMo Retriever is a new service in the NVIDIA NeMo framework and tool series. NeMo is a family of frameworks and tools for building, customizing, and deploying generative AI models. As a semantic retrieval microservice, NeMo Retriever uses NVIDIA-optimized algorithms to help generative AI applications make more accurate answers. Developers using this microservice can connect their AI applications to business data located in various clouds and data centers. This connection not only enhances the accuracy of AI applications, but also enables developers to process and utilize enterprise data more flexibly.
In summary, microservices such as NVIDIA's NIM and NeMo Retriever provide enterprises with an effective way to closely integrate AI models with business data to generate more Accurate and useful output. This provides enterprises with powerful tools to further promote the application and development of AI in various fields.
The cooperation between NVIDIA and Cloudera is opening a new door for enterprises , leading them to more efficiently utilize massive data to build customized collaborative assistants and productivity tools. Justin Boitano, vice president of enterprise products at NVIDIA, said: "The integration of NVIDIA NIM microservices with the Cloudera data platform provides developers with a more flexible and easier way to deploy large-scale language models, thereby promoting enterprise business transformation."
By simplifying the path from data to generative AI deployment, Cloudera and NVIDIA aim to accelerate enterprise adoption of transformative applications such as coding assistants, chatbots, document summarization tools and semantic search tools. . This collaboration builds on the two companies' previous efforts to leverage GPU acceleration by integrating NVIDIA RAPIDS into CDP.
Patel highlighted the business benefits of the expanded collaboration, stating: “In addition to providing customers with powerful generative AI capabilities and performance, the results of this integration will enable enterprises to The ability to make more accurate, timely decisions while reducing inaccuracies, hallucinations and errors in forecasts – all critical factors in navigating today’s data environment.”
Cloudera will demonstrate its new generative AI capabilities at NVIDIA GTC March 18-21 in San Jose, CA. As leading enterprises explore the potential of foundational models to transform their operations, Cloudera and NVIDIA believe their collaboration will position customers at the forefront of the emerging era of enterprise AI.
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