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THE EQUINIX INDICATOR
How Will Digital Infrastructure Enable Private AI?
Welcome to the first volume of The Equinix Indicator. A place for conversation around topics enterprises are prioritizing. In this volume, industry experts share their thoughts on how digital infrastructure will enable Private AI.
Jon Lin
EVP, General Manager, Data Center Services, Equinix
Industry Voices
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Interconnection
Interconnection provides hyperconnectivity to and from the digital core, ecosystems and the edge, helping enterprises reach more participants and services from clouds to data marketplaces.
Rajaneesh Kurup
Director, Equinix Research Group, Equinix
“AI processing will happen in a distributed manner at both the core clouds and at various types of edge locations close to where the data is generated or consumed.”
Steve Golik
Co-Founder & CEO, Juice Labs
Interconnected data centers are not just infrastructure; they serve as the backbone of a resilient digital ecosystem.
“Interconnection and ecosystems within a data center are crucial for AI implementations due to the high demands of GPU’s. 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.”
Steven Dickens
VP & Practice Lead, The Futurum Group
Effectively manage data privacy by limiting the need to transmit data to additional locations.
“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.”
Maribel Lopez
Founder & Principal Analyst, Lopez Research
The strategic imperative to connect with stakeholders, partners, and customers will not only support but enable the evolution of AI.
“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.”
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Sustainability
Sustainable practices are a top priority for enterprises exploring and implementing AI. There are two distinct angles to consider. Sustainable AI is about how enterprises will ensure they are building responsible practices into their AI deployments. On the other hand, AI for Sustainability is about how enterprises can use the power of AI for good.
Christopher Wellise
VP, Global Sustainability, Equinix
Efforts are being made to design, train and deploy AI responsibly to reduce the carbon impact of these technologies.
Sally Eaves
CEO, Tomorrow's Tech Today
The challenge to build sustainable AI brings digital infrastructure center stage.
“The intersection of AI and sustainability is an opportunity to create shared value. AI models hold promise to enable sustainable decision-making and accelerate ESG compliance. But for AI to deliver sustainability outcomes, it must first deliver on its own sustainability. In today’s ‘Age of (Gen)AI,’ this challenge to build sustainable AI brings digital infrastructure center stage. From moving to liquid-cooled solutions to collaborating on secure and scalable standards, data and digital infrastructure are differentiators that will empower enterprises to design and deploy AI sustainably. I anticipate the next trend of enterprise AI will be a focus on sustainability considerations baked right in.”
Linda Grasso
Digital Creator & CEO, @DeltalogiX
Driving economic growth and combating environmental and social challenges.
“In the quest for a digitally transformed future, businesses face the challenge of harmonizing innovation with responsibility. This involves embedding social and ecological awareness into the core of enterprise AI, paving the way for a future where technology propels business while protecting our planet and society.
Developing digital infrastructures that support advanced technologies like AI and are sustainable, efficient, and secure is essential. This requires investments in green energy solutions, optimization of digital resource usage, and robust data protection measures.
Such an approach transforms enterprise AI into a dual force: driving economic growth and combating environmental and social challenges. It fosters a holistic strategy that values innovation and sustainability, ensuring a balanced and responsible technological advancement.”
Helen Yu
CEO, Tigon Advisory
AI algorithms explicitly designed for sustainability are emerging.
“Envisioning trends in sustainable AI involves anticipating innovations that reduce AI’s energy consumption and environmental impact. AI algorithms explicitly designed for sustainability are emerging, emphasizing both performance and energy efficiency. Additionally, expect advancements in hardware, like energy-efficient processors tailored for AI tasks. Staying ahead means continuously monitoring these trends and proactively adopting eco-friendly technologies and methodologies. At the intersection of AI and sustainability, standout areas include AI-enabled resource optimization. Through digital infrastructure AI-modeling, enterprises efficiently manage energy consumption and predict climate change impacts. AI-driven initiatives optimizing supply chains for reduced carbon footprint and waste management also hold significant potential in fostering sustainability.”
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