Key points:
• IBM is expanding its support for Nvidia technology, integrating its Watsonx development platform with Nvidia Inference Microservices (NIM) software.
• IBM is adding Nvidia awareness to its content-aware storage technology, allowing for faster querying and data augmentation.
• IBM is also launching IBM Cloud instances with Nvidia H200 GPUs, enabling customers to train larger AI models and process large datasets in real-time.
As a technology reporter, I’m excited to share the latest news from the world of artificial intelligence and Microsoft’s rivals. In a significant development, IBM has announced a major boost for its support of Nvidia technology, aiming to help enterprises increase their AI production and storage capabilities.
According to a statement from IBM, the company is integrating its Watsonx development platform with Nvidia Inference Microservices (NIM) software. This move is designed to simplify the deployment of AI models, including inference engines like Triton Inference Server, TensorRT, and PyTorch. By combining IBM’s Watsonx with NIM, organizations can now monitor and govern Nvidia NIM microservices across any hosting environment.
In addition to this major software announcement, IBM is also expanding its content-aware storage technology with Nvidia awareness. This enables faster querying and data augmentation, making it easier for organizations to update AI tools and improve their performance. IBM’s Storage Scale platform, which was introduced recently, will now support CAS and respond to queries using extracted and augmented data. This will speed up communication between GPUs and storage, utilizing Nvidia BlueField-3 DPUs and Spectrum-X networking.
On the cloud front, IBM has also launched IBM Cloud instances with Nvidia H200 GPUs. These instances will enable customers to train larger AI models and process large datasets in real-time, improving the accuracy of predictive analytics and data-driven decision-making. IBM claims that the H200 Tensor Core has increased memory bandwidth, allowing it to handle larger datasets, and is highly energy-efficient, with a lower total cost of ownership.
Finally, IBM Consulting is adding Nvidia Blueprint to its AI Integration Service, which offers customers support for developing, building, and running AI environments. This move further reinforces IBM’s commitment to AI and its partnership with Nvidia, as the company aims to make it easier for organizations to integrate NIM microservices with its other services.
Overall, this new partnership between IBM and Nvidia has the potential to revolutionize the way organizations approach AI development and deployment. With these new features and capabilities, businesses can now leverage the power of AI to improve their operations and gain a competitive edge in their respective markets.
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