Penguin Solutions’ Global Marketing VP Mark Seamans, “AI Currently Entering 2nd Wave with Business-specific Customization.”

SKT is driving cooperation with Penguin Solutions, a leading American integrated AI data center solutions provider. At CES 2025 held in January, SKT signed a cooperation agreement with SK hynix and Penguin Solutions for joint R&D and business promotion of AI data center solutions [see article here]. In July of last year, SKT made its largest AI investment to date amounting to 200 million USD[see article here].

SKT Newsroom interviewed Mark Seamans, Global Marketing VP of Penguin Solutions, on the company’s business strategy, the outlook on AI infrastructure, and the significance of the cooperation with SKT. Mr. Seamans has deep technical mastery and leadership experience in designing and implementing complex enterprise infrastructures such as cloud computing, AI, big data storage, high-performance computing (HPC), and business process management. Drawing from his extensive technical experience, he is responsible for developing and driving Penguin Solutions’ global marketing strategy.

* This article contains the opinions of other companies and may differ from SK Telecom’s official position.

Infrastructure is key to AI growth, even more critical in enterprise markets adopting AI for competitive advantage

Mark Seamans, Global Marketing VP of Penguin Solutions

Q. The AI ecosystem is rapidly taking shape. How do you expect AI to change the industry in the future?
AI is driving fundamental change within virtually every industry based on its ability to drive efficiency and effectiveness across product and services segments. Within the product space, AI is advancing the way that researchers pursue the exploration of new breakthroughs ranging from drug discovery to personalized healthcare—and product teams are benefitting from both concept refinement and actual design acceleration.

Up to this point, many organizations have been focused on exploring AI capabilities, identifying potential use cases within their markets, and beginning to understand how and where to source the critical enterprise AI data that is required to train and finetune models that will support initial deployments. These initial steps tend to occur somewhat slowly at first, but they provide the foundation for accelerated deployments in the very near future. AI adoption is expected to evolve from this experimental stage to become a core business tool and we believe that enterprises will soon see end-to-end control of their own sovereign AI infrastructure as a competitive requirement.

For example, we are engaged with early-adopter customers in the financial services marketplace who began their AI journey when the technology first entered the spotlight. To date they have identified many use cases across their business where the technology can drive improvements that range from incremental to transformational.

Running AI training and inferencing processes on generic virtualized environments within the public cloud may not provide the level of performance, responsiveness, and control that enterprise IT leaders desire. As AI technology becomes a core corporate asset, enterprises will come to view bespoke AI infrastructure as a key strategic advantage. However, many aspects of AI infrastructure deployments—particularly when done at scale—present new challenges for enterprise IT teams given that many of the hardware, software, and process elements are new and different.

Given these trends and potential business impacts, we expect that AI will change the enterprise IT infrastructure delivery industry by opening a significant new opportunity for specialists in high-performance computing, accelerated networking, and AI-specific system management. This initial phase will focus on enabling enterprises to deploy their near-term core infrastructure, but the pace of change and innovation within the marketplace will also create opportunities for solution providers such as Penguin Solutions that can continually consume the latest capabilities and translate them into technology advantages for our customers.

Q. What role do you think AI infrastructure will play in this ecosystem? Specifically, how do you think the size or trends of the AI DC market, which will play a key role, will change?
Infrastructure is at the heart of AI growth—particularly within the enterprise market, where corporations will look to AI for differentiation and competitive advantage. If we think of AI as a car, then infrastructure is the engine and transmission that powers the driving experience.

At Penguin Solutions, we have consistently spoken about AI emerging in a series of “waves” as different market segments invest in the technology over time.

The first wave involves large-scale foundational model development, with companies making large investments in AI training systems to build out the core models that enable a new level of AI capability. Penguin Solutions has worked with leaders such as Meta to participate in the design, build, deployment, and ongoing management of the clusters that have been used to train major industry AI models such as Llama. These deployments can be very large and Penguin Solutions has significant experience in how to optimize deployments at scale.

However, most enterprises will not need this massive level of infrastructure. The second wave of AI adoption is about enterprise-level deployments and enabling organizations to build on models developed during the first wave to create application-optimized models for specific use cases. These models can be trained and finetuned with mid-sized or large-scale infrastructure, using insights from specific enterprise data to power automation and more efficient business operations. The design, build, deployment, and management of these customer-specific solutions is a specialty area for Penguin Solutions.

The third wave of adoption focuses on AI inference at scale, leveraging models from the first two waves – making every AI-driven organization a part of Wave 3 at some level. Some use cases will require modest inferencing configurations. Others will involve massive, mission-critical“Mission critical” refers to a characteristic or condition that, if not functioning properly or destroyed, could have a fatal impact on the entire business operation and cause disastrous impact to the organization or society. This includes the telecommunication system of an online business company, a disaster communication network, and an aircraft operation control system. systems. The system architecture, processor, and network options for inference solutions are far more varied in this wave. Customers may elect to deploy some systems at “the edge” close to where data generation is occurring.

Helping customers understand and navigate this broad set of AI infrastructure decisions is a core part of Penguin Solutions’ value proposition to its customers. Our goal is to become a trusted advisor on AI infrastructure and long-term partner for our customers so that they can leverage AI for their competitive advantage.