October 2023: The latest offering in the IBM Storage for Data and AI portfolio, the IBM Storage Scale System 6000 is a cloud-scale global data platform designed to meet the data intensive and AI workload demands of the present day. Recognized for its vision and implementation, IBM is a Leader in the Gartner Magic Quadrant for Distributed File Systems and Object Storage for the seventh consecutive year and counting in 2022.1 Designed for data-intensive use cases, the new IBM Storage Scale System 6000 aims to further solidify IBM's leadership position with an enhanced high-performance parallel file system.
It offers 256GB/s throughput and up to 7M IOPs per system for read-only workloads in a 4U (four rack unit) footprint.
In order to capitalize on the economic benefits offered by both foundation and traditional AI models, organizations must direct their attention towards the data itself. This includes optimizing future investments in data storage, addressing concerns such as capacity and growth projections, data location, security, and access. The IBM Storage Scale System 6000 enables customers to do precisely that by integrating data from the core, edge, and cloud into a single platform with GPU workload optimization.
February 2024: Lenovo™ and Anaconda® Inc., the foremost provider of the most popular artificial intelligence (AI), machine learning (ML), and data science platforms in the world, reached an agreement in February 2024 to equip Lenovo's high performance data science workstations. The collaboration will merge the reputable and dominant ThinkStation™ and ThinkPad™ workstation product lines of Lenovo with the enterprise-level capabilities of Anaconda, which include leadership in open-source solutions, security, and dependability. The realm of artificial intelligence, encompassing deep learning and generative AI, is presenting data scientists and businesses with novel prospects.
Open-source software and cloud-based solutions are largely responsible for the current AI innovation, with Python being the most popular programming language for AI applications. Many organizations, nevertheless, are reassessing their investment strategies in AI development due to the data security risks, privacy concerns, and frequently prohibitive costs of cloud-based AI solutions that are linked to the enterprise-level use of open-source software.
March 2022: An organization called Panasas, which offers high-performance storage, announced that its PanFS software lineup will now include more data insight and mobility tools. Organizations using high-performance computing (HPC), high-performance data analytics (HPDA), and artificial intelligence and machine learning (AI/ML) workloads at scale should benefit from the improved visibility and portability of data assets provided by the preview and PanMove software solutions. They provide Panasas storage with data management and analytics tools.
January 2022: To make it simpler and faster for users to handle and analyze data on a petabyte scale, AWS added five new features to its database and analytics portfolios. Customers would find it simpler to run high-performance database and analytics workloads at scale thanks to these new features for Amazon Document DB, Amazon OpenSearch Service, and Amazon Athena.
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