How Private Network Connections Enable Private AI Success

Industry experts discuss how interconnection will play a vital role in the growth of enterprise AI

How Private Network Connections Enable Private AI Success

Since the explosion of generative AI into the mainstream, a growing number of AI models are being developed and hosted in the public domain. But for enterprises, this approach raises concerns around risk and data protection. As organizations look for opportunities to use AI for competitive advantage, they’re now developing new AI strategies that factor in the need to protect their sensitive data.

Private AI is an emerging trend that enables companies to safeguard proprietary data, reduce regulatory risk and optimize AI performance. But to enable private AI, you need the right core infrastructure, with proximity to public clouds, access to ecosystem partners and providers, and global reach. Once you have the right data architecture in place, with an authoritative data core, you need to ensure secure, low-latency connectivity across that digital core and your ecosystem in order to reach more participants and services. As AI grows in popularity, no doubt AI ecosystems will continue to grow too.

Private AI requires private exchange of data between organizations in an AI ecosystem. This is what we call interconnection—the direct, private connections between counterparties. To succeed with private AI, companies must enable data ingestion from multiple sources, optimize data transfer speeds between public clouds and private resources, and accelerate actionable insights. And that means they need hyperconnectivity across their hybrid environment.

The Equinix Indicator

In the first volume of The Equinix Indicator industry experts share their thoughts on Digital Infrastructure and Private AI.

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To further explore the importance of interconnection for private AI, we spoke with four industry experts to get their take on how private interconnection empowers companies to excel at AI. Here’s what they had to say:

Private AI requires a collaborative environment where ecosystem partners interact and contribute to the development of technologies

Rajaneesh Kurup, Director, Equinix Research Group, Equinix — @rajaneeshkurup

AI amplifies connectivity requirements beyond normal volumes. A collaborative environment where technology providers, developers and partners can interact and contribute to the development of technologies is key to building a successful AI strategy. Ecosystems and interconnection will play a vital role in enabling the evolution of your AI strategy. Interconnection supports data injection from multiple sources, optimizes data transfer speeds between clouds and private resources, and accelerates the distribution and automation of real-time actionable insights.

Interconnected data centers are not just infrastructure; they serve as the backbone of a resilient digital ecosystem

Steve Golik, Co-Founder & CEO, Juice Labs

Interconnection and ecosystems within a data center are crucial for AI implementations due to the high demands of GPUs. Taking advantage of direct data center interconnection gives the bandwidth and latency optimizations needed to reach the next level of performance, enabling seamless data exchange. Interconnected data centers are not just infrastructure; they serve as the backbone of a resilient digital ecosystem.

Effectively manage data privacy by limiting the need to transmit data to additional locations

Steven Dickens, VP & Practice Lead, The Futurum Group — @StevenDickens3

Harnessing an ecosystem approach when establishing private AI initiatives ensures that enterprises not only meet current demands but also evolve and optimize with the technological landscape. This approach involves interconnecting components throughout the AI ecosystem and fostering low-latency connections, and supporting the efficient distribution of heavy workloads with the benefit of enhanced scalability. This environment enables enterprises to effectively manage data privacy by limiting the need to transmit data to additional locations.

The strategic imperative to connect with stakeholders, partners and customers will not only support but enable the evolution of AI

Maribel Lopez, Founder & Principal Analyst, Lopez Research — @MaribelLopez

Successful private AI isn’t built in isolation, it’s a collaborative effort that spans cloud and on-premises technology. Enterprises are looking for scalability and flexibility when it comes to implementing, securing and expanding their private AI capabilities, which is where interconnection and ecosystems come into play. The strategic imperative to connect with stakeholders, partners and customers will not only support but enable the evolution of AI.

Learn more about how digital infrastructure is enabling private AI

No doubt, hyperconnectivity will become even more important as organizations connect to more partners, service providers and other ecosystem participants in their AI future.

For more information and ideas on how digital infrastructure can empower companies to succeed with AI, check out the Equinix Indicator, where industry leaders discuss the topics enterprises are prioritizing. Here you’ll learn more about the data architectures and connectivity trends that are fueling the AI future, as well as how to develop sustainable AI practices.

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