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In today’s rapidly evolving financial services industry, integrating artificial intelligence has become essential for gaining a competitive advantage and enhancing operational efficiency.

However, the path to successful AI deployment at scale has its complexities, encompassing challenges such as data security, performance optimization, and resource management. Financial institutions must carefully consider their approach to AI implementation, whether on-premises or in the cloud, as they strive to maximize their investments while mitigating potential risks. Establishing an AI Center of Excellence (CoE) is the key to meeting these challenges head-on, providing the necessary framework to harness the full potential of AI while ensuring adaptability to various deployment scenarios. In this dynamic landscape, an AI CoE becomes the linchpin for FSI companies seeking to navigate the AI journey effectively and emerge as leaders in the era of AI-driven finance, and this is why we created the Enlighted Leader’s Guide to AI in Finance.

What is an AI Center of Excellence (CoE)?

Before we start, let us clarify what we mean by saying “AI Center of Excellence.” This epitomizes AI infrastructure best practices, available on-premises or in a hosted private cloud environment. It is a purpose-built infrastructure for powering and scaling company AI initiatives most effectively, optimizing for performance, longevity, and return on investment. This proven model for infrastructure comes from DDN’s decades of experience in high-performance computing and the joint expertise of lasting partnerships with industry-leading companies for accelerated computing and networking.

Crafting a Swift and Agile AI CoE for Unparalleled Time-to-Market Success

In the financial services industry context, an AI CoE takes on a specialized role that aligns with the sector’s need to adapt quickly to changing market conditions. Whether companies opt for on-premises or cloud deployment models, this center of excellence can expedite AI training cycles and time to results, translating into faster time-to-market success through specific engineering choices. Considering the hardware infrastructure carefully is crucial to ensure the CoE’s effectiveness in expediting AI training cycles and achieving improved time-to-market. While lightning-fast GPUs are an easy decision here, storage is an equally vital component that often gets overlooked. Ensuring your storage can keep up with your top-of-the-line processors is essential to maximizing time-to-insight, model training cycles, and subsequent time-to-market success. Also, for hosted solutions, knowing the GPUs are fully saturated ensures you are getting the most from your cloud spending.

Make the Right Decision to Avoid Costly Mistakes with Generative AI & LLM Deployment

Why DDN?

Whether deploying on-premises or in the cloud, DDN’s storage infrastructure product line is the industry standard for accelerating time-to-insight and model training cycles.

For on-premises deployments, DDN’s AI400X2 storage systems far outpace the competition with read and write speeds of up to 90 GB/s and 65 GB/s, respectively. This increased performance translates to average reduction times of 10x for model training time and time to insight. For comparison, typical NFS-based storage is limited to read and write speeds of 2 GB/s and requires much more energy and rack space.

Additionally, those who opt for DDN AI400X2 storage systems benefit from faster checkpointing, used for larger AI models where training progress is saved at various intervals in the training cycle. In the event of interruptions or failures, the training process can resume from the last checkpoint, conserving time, computational resources, and ensuring consistency in model outcomes. Checkpointing is also used to save last-known-good models for later reference. With the ability to resume training from the last checkpoint, financial institutions can ensure that their models continue to learn without unnecessary setbacks. By speeding up checkpointing, DDN can save as much as 12% of model run times to deliver higher productivity.

Checkpointing for Large Models: Protecting Against Failures & Network Issues

Your AI Infrastructure: Upgraded

In the rapidly evolving world of financial services, where success hinges on staying ahead of the curve, establishing an AI CoE is a strategic imperative. Whether deployed on-premises or in the cloud, this purpose-built infrastructure is your ticket to swift adaptation and unparalleled time-to-market success.

With DDN as your technology partner, you are not just investing in a solution; you are investing in leading your industry. Our expertise and technology solutions empower you to harness the full potential of your AI initiatives and stay ahead in the AI-driven financial landscape. Swift adaptation, faster insights, and evolving AI models are well within your reach. Choose DDN and accelerate your journey to AI excellence. Your competitive advantage awaits.

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