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Thrive in Challenging Times with AI

Patrick Lastennet, Director of Enterprise Business Development, Interxion

24 July 2020

Amidst unprecedented times and an increasingly challenging economic environment it’s imperative for businesses to prioritise digitalisation to protect customer loyalty, reduce costs where possible, and rise above competitors. Artificial intelligence (AI) is uniquely poised to help businesses achieve all three objectives, but many enterprises do not know how to effectively translate design to operation.

Leveraging AI requires an enterprise-ready data and infrastructure strategy, but unfortunately, 76% of businesses regard infrastructure as an obstacle to AI success. In fact, we often see enterprises investing in AI development, but they never actually reach the deployment phase, which is a waste of time, resources and money. To help businesses get a better sense of how to effectively leverage AI, Interxion recently hosted a webinar illustrating how to improve the end to end production from artisanal AI to mechanised AI that can be integrated into any standard IT operations within the enterprise. 

Tony Paikeday, Director of Product Marketing for Artificial Intelligence and Deep Learning at NVIDIA, kicked off the discussion by outlining why infrastructure matters for AI in the context of digital transformation. Paikeday highlighted some of the many use cases that can provide companies with a cutting edge in difficult times, such as recommended systems, industrial inspection, and AI-enabled analytics.

He also discussed how lack of adequate compute results in a serious slow-down for developers as they work to design the best AI technology. Many organisations are leading remarkable AI research and development, but without input from IT. The IT approach used to build conventional software models does not map to AI development. Without a fine-tuned IT strategy and proper compute resources in-house, teams tend to produce shadow AI – AI infrastructure created under IT’s radar, which is challenging to successfully operationalise and ultimately unproductive. CIOs can get ahead of shadow AI by leading with an infrastructure strategy that will accelerate the design to deployment cycle.

Ivan A. Coetzee, Head of AI Collaboration at Scan Computers International Ltd, went over some of the challenges that come for customers on their AI journey from desktop to data centre. He detailed potential roadblocks at the development stage, as well as the need to accelerate IT teams’ understanding of the latest tech, focus on the stack of technology required for success, and work with a sophisticated data centre partner.

Patrick Lastennet, Director of Enterprise Business Development for AI at Interxion, highlighted the importance of enterprises working with data centres that can provide enough power to support AI development. Most data centres can support 15kW per rack, however AI workloads require 20kW - 40kW per rack and the associated cooling. As this requirement is expected to jump to 80kW by 2023, Patrick explained why it’s vital for enterprises to have an infrastructure partner in their corner.

Working with a data centre partner, particularly one outfitted with NVIDIA technology like Interxion, wraps together all of the infrastructure enterprises need to leverage AI and level-up their digitalisation journey. Interxion’s data centres are designed with features critical to successful AI infrastructure, such as energy efficient equipment and innovation for sustainable operation. The interconnected campuses allow companies to hyper-scale and distribute AI across regions, supported by direct access to a connected community of customers, partners, networks and clouds. Leveraging interconnection data centres like Interxion’s supports a full AI lifecycle, ensuring technology moves from design to deployment.

To watch the full webinar and learn more about how greater infrastructure and position your enterprise for AI deployment, click here.