Rohit Badlaney | General Manager, IBM Cloud Products and Industry Platforms
May 21, 2024
Companies across all industries are constantly exploring new ways that artificial intelligence (AI) can support business innovation and growth. According to an IBM survey, a majority of executives say their organizations need to quickly adopt generative AI (Gen AI) to accelerate innovation. However, only 39% of organizations currently implement or operate Gen AI for innovation and research. Many organizations lack the infrastructure and skills to properly manage the data and deployment challenges associated with these compute-intensive workloads.
IBM Cloud helps you gain a competitive edge with the combined power of a hybrid cloud and AI stack. Our enterprise cloud platform is also built for the most regulated industries and, when combined with our high performance computing (HPC) heritage, provides unique capabilities that can support the AI infrastructure required for performance-critical workloads. I'm in a position. We are working on several new solutions and customized collaborations to enable seamless and secure integration of AI.
David Tan, CrushBank CTO:
“For CrushBank, it is important to us that we deliver on our promise of a great customer experience. The combined power of cloud and AI is revolutionary in this space. By leveraging WatsonX on IBM Cloud for our AI Knowledge Management platform, we can serve customers faster and more effectively, reducing overall time to resolution by 45% while reducing IT complexity while ensuring security and compliance objectives. I was able to achieve this.”
Momentum for performance-driven computing: Training and running AI models
Over the past few years, IBM has announced several products that support training and inference of generative AI models. IBM Research announced Vela, IBM's first AI-optimized cloud-native supercomputer, powered by NVIDIA A100 Tensor Core GPUs and hosted on IBM Cloud. Vela is designed to scale up on demand and easily deploy similar infrastructure into his IBM Cloud data centers, enabling IBM to work with partners to train generative AI models. . Vela's main mission last year was to train IBM's Granite models and drive AI development. Last year, IBM also announced the availability of his NVIDIA GPU product (NVIDIA A100 Tensor Core) on IBM Cloud. Clients use it for enterprise-class underlying model inference via the watsonx service or as GPUaaS for specific needs.
We are also working with IBM Research and Red Hat on several initiatives to support the implementation of generative AI. IBM Cloud's GPU infrastructure is used to support InstructLab, an open source AI project that trains watsonx Granite models and facilitates contributions to large-scale language models (LLMs). Granite is IBM's flagship series of LLM foundation models, trained on trusted data from companies across the internet, academic, code, legal, and finance. IBM Cloud also adds support for Red Hat Enterprise Linux AI (RHEL AI) and Red Hat OpenShift AI platforms, which enables users to more seamlessly develop, test, and deploy Gen AI models.
Joe Fernandes, Vice President and General Manager, GenAI Foundation Model Platforms, Red Hat:
“We need to make GenAI innovation accessible to more users in more organizations, and that means lowering the barriers to contributing to and coordinating LLMs. Launched in collaboration with IBM The RHEL AI and InstructLab project will do just that by making AI models more accessible to a broader community of users, including domain and subject matter experts, anywhere in the hybrid cloud.”
Building on GPU Momentum: Inferencing with NVIDIA L4 and L40S GPUs
IBM is expanding its NVIDIA GPU offering on IBM Cloud and is one of the first cloud providers to offer NVIDIA L40S. IBM Cloud also offers NVIDIA L4 Tensor Core GPUs that support both AI and other accelerated workloads, including 3D graphics and video applications. This enables customers to add these to their enterprise cloud platforms using NVIDIA AI Enterprise software, which is optimized to address the needs of mission-critical workloads across resiliency, performance, security, compliance, and total cost of ownership. You can now deploy GPU instances on demand. .
Direct access to NVIDIA GPUs on IBM Cloud in VPC and managed Red Hat OpenShift environments gives clients the flexibility to choose the right accelerator for AI training, fine-tuning, and inference. This helps reduce the cost of running AI-powered applications. NVIDIA GPUs can be integrated with data and AI platforms and services on IBM Cloud, including watsonx, to help you build, scale, and manage AI. IBM Cloud expects the latest his NVIDIA Blackwell platform to also be available in the first half of 2025.
Later this year, IBM Cloud will add NVIDIA H100 GPUs based on the NVIDIA Hopper architecture to nine regions in Washington, DC and Frankfurt, Germany where you can cluster multiple systems. He also plans to introduce NVIDIA H200 Tensor Core GPUs in some regions early next year.
Accelerate automation with deployable architecture
In addition to working with partners, IBM provides customers with a unified enterprise platform experience with a set of preconfigured patterns to help automate solution delivery. Deployable Architecture (DA) provides quick, easy, and secure preconfigured deployment automation for IBM products on IBM Cloud. Our mission with these preconfigured products is to make it easy for businesses and developers to achieve results in hours while supporting their security and compliance goals. Addressing the risks and burdens of implementation allows clients to redirect resources to their own businesses.
IBM Cloud is on a mission to drive AI and hybrid cloud innovation for our clients. We have the infrastructure to train our own models, the deep skills of IBM Consulting, and a hybrid cloud strategy that allows our clients to drive tangible business value and harness the potential of generative AI. We will help you define and implement it. Our solutions are designed to help transform the way enterprises, developers, and open source communities build and leverage generative AI.
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Statements regarding IBM's future direction and intentions are subject to change or withdrawal without notice and represent goals and objectives only.
