Data storage equipment maker NetApp Inc. and Nvidia Corp have launched Ontap AI, which gives organisations working on artificial intelligence projects complete control of their data, from edge to core to cloud, said a press statement.
“Ontap AI creates a single data environment for AI,” said Octavian Tanase, senior vice-president, Ontap, NetApp. “This gives customers the control, access, and performance they need to provide the right data at the right time at the right location to their AI applications – all at scale and all integrated, managed, and protected by the NetApp Data Fabric,” Tanase added.
Although many organisations currently have advanced AI platforms and tools in place, they lack control over access to their own distributed data stores, limiting complete and real-time access to their AI projects, which train on data.
“Success with AI depends on a business’s approach to data. To be effective in today’s AI use cases and to future-proof a business for new AI applications, organisations must achieve visibility into and control of their data, from edge to core to cloud,” added the press statement.
Ontap AI is powered by NetApp’s AFF A800 cloud-connected flash storage and Nvidia’s DGX supercomputers, said the press statement.
The platform aims to accelerate access within the hybrid cloud, which can be defined as a mix of data an organisation’s AI tool is fed from across its various data stores including on-premises data, private cloud and third-party public cloud services.
Ontap AI helps organisations to implement and scale up Deep Learning using a modular approach, said a blog by Nvidia. Deployment time for AI gets shrunk from months to days, added Nvidia.
The platform is an optimal architecture for AI and Deep Learning, the blog said. It eliminates the guesswork of designing infrastructure, providing an optimal configuration of GPU computing, storage and networking. GPU is graphics processing unit.
Companies are making significant inroads into using AI to solve real-life problems. “However, while very exciting, AI models and workloads are not easy to deploy, and many organisations are struggling,” said Ritu Jyoti, program vice-president, IDC, a research firm.