May 13, 2024 By Edward Calvesbert 3 min read

AI adoption is paramount in today’s business organizations, but the path to AI adoption can be filled with curves, bumps and uncertainty. Enterprise-ready SaaS environments may not be appropriate for highly sensitive data and applications for some companies, especially those in regulated industries.

Many organizations have built on-premises infrastructure and processes to accommodate their security and data sovereignty requirements. But while these systems have been engineered to support more traditional enterprise IT workloads, they are often ill-prepared for the intense requirements of AI at enterprise scale.

For most organizations, enterprise data exists in on-premises silos of systems of record; enterprise data warehouses, data lakes, and cloud-based solutions. Moving data is risky, costly, inefficient and impractical in a world where everyone needs access to data in real-time. Moving on-premises data to the cloud for AI projects is typically a nonstarter due to cost, latency, data governance or other issues. Organizations need a simple, cost-effective and efficient way to deploy AI on-premises.

Deploying AI at  enterprise scale means running a sophisticated convergence of software anddata, built on containers and deployed on a modern, hybrid-cloud infrastructure. We have seen organizations turning to advanced hyperconverged systems. These systems are optimized for creating and rapidly deploying new, modernized business applications. Moreover, they run effectively on an open, hybrid-cloud platform, such as the Red Hat®  OpenShift® Container Platform.

Announcing Fusion HCI for IBM’s AI and data platform, watsonx™ 

We’re happy to announce that clients can now take advantage of IBM® Fusion HCI and IBM watsonx™ to enable easier on-premises AI deployments. This solution is designed to offer tight integration, ease of management, and consistently high performance across a wide range of AI and data workloads.

Clients across a broad set of business domains, such as customer service, manufacturing, marketing, human resources, and more, are implementing popular AI use cases and generative AI patterns. These applications, which include summarization, content generation, insight extraction and Retrieval-Augmented Generation (RAG) are designed to connect AI with data workloads. This integration helps to deliver more insightful and dynamic information to end users.

Businesses are also seeking enterprise-grade foundation models in the hope of delivering greater performance and cost-effectiveness with their sensitive data. The watsonx model library provides multimodel choice and flexibility that spans open source, third-party commercial models like Meta’s Llama 3, open-source Granite models and IBM customized Granite models, and bring your own models (BYOM) to support a broad range of enterprise domains and use cases. The platform provides the necessary GPUs to facilitate rapid model availability and performance for on-premises environments.

AI governance with watsonx.governance™ is integrated into the solution to provide AI model lifecycle management and facilitate oversight and monitoring of AI model usage. These capabilities help organizations measure the accuracy of LLM outputs and their overall efficiency for increased scalability and accountability across the entire AI lifecycle. IBM offers a solution that combines watsonx.data and IBM Fusion HCI, allowing organizations to efficiently manage and analyze large data sets for AI. This open data lakehouse architecture is cost-effective compared to traditional data warehouses and delivers improved performance through faster querying of data stored in low-cost object storage.  

Why Fusion HCI for watsonx?

IBM Fusion is a platform for Red Hat OpenShift, an industry-leading container management and orchestration platform. Organizations deploying Red Hat OpenShift applications should be aware that some AI and data workloads can only be deployed on-premises; sensitive data requires extra privacy and governance. IBM Fusion HCI combined with watsonx creates a secured on-premises engineering environment with the flexibility of the hybrid cloud. IBM Fusion simplifies deploying Red Hat OpenShift applications with the watsonx platform to help streamline AI and data science, application development, data management, and data and AI governance workloads.   

IBM Fusion HCI includes data services built for client’s enterprise applications and Red Hat OpenShift. These services are designed to simplify infrastructure and data management, providing platform engineers with a unified view to manage hardware and software resources, including backup and restore, high availability (HA), and disaster recovery (DR) for mission-critical applications. These Fusion data services aim to make data within containerized applications remain accessible and persistent with a backup workflow engine that enables users to define workflow orchestrations or ‘recipes’ for performing complex backups.

IBM Fusion HCI with watsonx supports GPU-accelerated applications through its integration with NVIDIA L40S and H100 GPU servers. This allows organizations to streamline and boost AI and compute-intensive machine learning (ML) and generative AI workloads. Clients now have a simpler way to bring their AI workloads closer to their data and applications in data centers and at the edge.

Getting started

For more information about watsonx, IBM’s AI and data platform, visit the product page. To learn more about how to achieve your application modernization initiatives with IBM Fusion HCI, download the free report.

Explore the interactive watsonx.ai demo

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