DDN BLOG

AI and the Rise of Intelligent Infrastructure Platforms

Businesses in every market recognize Artificial Intelligence as a critical business priority. Research shows time and again, companies that can scale AI, and implement it in production, are seeing enormous returns on their investments. Other businesses are struggling to reach important milestones or failing to scale workloads in production.

To create meaningful business change, AI requires a clearly defined data-led approach.  How that data is collected, managed, and analyzed is a cornerstone consideration for companies who see the application of AI to their industry as the key differentiator.  From real-time decision-making and breakthrough research to better customer service, AI is ready to amplify value and create new opportunities for businesses prepared to take advantage.  Making the right infrastructure choice is essential to maximizing productivity and managing costs as applications grow over time.

Cloud deployment might look attractive initially and may in fact be fine for some applications long term, while other more data-intensive applications will require on-premises deployment due to latency, performance and overall cloud services costs. Legacy infrastructure systems might also look attractive due to IT’s familiarity with their operation. Still, these systems are not designed to sustain the performance or handle the capacity required by AI data, nor are they intended to supply an end-to-end application service for AI.

Many companies encounter numerous roadblocks while implementing new applications, gathering data and scaling with success, but it doesn’t have to be that way. Enter “Intelligent Platforms”. If you look deeper into the

2021 Gartner® Hype CycleTM for Infrastructure Strategies, you will see that Intelligent Platforms are beginning to emerge to drive administration, application and automation capabilities that are essential to effectively supply agile services that deliver the performance and scalability required by AI. We believe that this represents a strategic opportunity for our customers: our key takeaway from the report is that Gartner predicts that it still might be 5-10 years before mainstream adoption of Intelligent Platforms, while early movers will have a distinct advantage over slow adopters.

 

 

DDN in collaboration with NVIDIA, supplies Intelligent Platforms dedicated to high performance and data-intensive workloads like AI and analytics.  DDN’s A3I with NVIDIA POD and SuperPODTM systems supply tightly integrated infrastructure to make acquisition, deployment, management and growth far simpler, cost effective and sustainable over time. Continuous enhancements are further optimizing the data path, creating more secure environments and simplifying the deployment of cloud-like services for AI.

Get your copy of the 2021 Gartner® Hype CycleTM  for Infrastructure Strategies here. And contact a DDN expert to get a consultation on your AI Infrastructure needs today (consulting@ddn.com).

About DDN

DDN is the world’s largest private data storage company and the leading provider of intelligent technology and infrastructure solutions for Enterprise At Scale, AI and analytics, HPC, government and academia customers. Through its DDN and Tintri divisions the company delivers AI, Data Management software and hardware solutions, and unified analytics frameworks to solve complex business challenges for data-intensive, global organizations.

DDN provides its enterprise customers with the most flexible, efficient and reliable data storage solutions for on-premises and multi-cloud environments at any scale. Over the last two decades, DDN has established itself as the data management provider of choice for over 11,000 enterprises, government, and public-sector customers, including many of the world’s leading financial services firms, life science organizations, manufacturing and energy companies, research facilities, and web and cloud service providers.

  • Kurt Kuckein
  • Vice President, Marketing
  • Date: October 14, 2021

This site uses cookies. Please see our Privacy Policy to learn more about how we use cookies and how to change your settings if you do not want cookies on your computer. By continuing to use this site without changing your cookies settings, you consent to the use of our cookies. Privacy Policy