Generative AI is transforming industries by pushing the boundaries of what technology can achieve, from creating lifelike images to producing human-like text. However, behind this impressive tech lies a significant challenge—these AI models need an immense amount of computational power, storage, and cooling to run efficiently. That’s where colocation data centers come into play. Let’s dive into why these facilities are so essential for the AI revolution, particularly for companies like Sharon AI, which are leveraging this infrastructure to deliver cutting-edge AI solutions.

What Are Colocation Data Centers?

Colocation data centers, often called “colo” for short, are shared facilities where businesses can rent space to host their own servers and IT infrastructure. These centers provide critical resources like cooling, power, network connections, and physical security, which are all necessary to ensure seamless operations. Instead of building and maintaining their own data centers, companies can lease space in these colocation facilities, significantly reducing costs and simplifying infrastructure management.

Businesses ranging from startups to large enterprises use colocation to expand their computing capacity without investing in building new data centers. By sharing space with other organizations, companies benefit from lower operational costs and access to state-of-the-art infrastructure, all managed by experts.

Why Is Colocation Ideal for Generative AI?

Generative AI models, like those used in deep learning and large language models, require heavy computational resources, particularly GPUs, to function efficiently. Here’s why colocation is the perfect fit for these AI workloads:

Scalability

As AI models grow in complexity, they demand more hardware. Colocation centers offer scalable infrastructure, making it easy for companies to add more servers or upgrade their hardware without the hassle of expanding physical spaces.

Power and Cooling

Running AI models at scale consumes a tremendous amount of power and generates significant heat. Colocation facilities are designed to handle these demands with robust cooling systems, ensuring hardware operates at optimal temperatures.

Security and Compliance

AI applications often deal with sensitive data. Colocation centers provide multiple layers of security, both physical and digital, ensuring that data remains safe and compliant with industry regulations.

Cost-Effectiveness

Building and maintaining an in-house data center is costly. Colocation offers a more budget-friendly alternative, allowing businesses to lease the resources they need without a hefty upfront investment.

Expert Support

Colocation providers employ skilled engineers and IT staff who can assist with deploying and managing AI models, reducing the burden on in-house teams.

What Are the Key Benefits of Using Colocation for AI Workloads?

For companies looking to deploy AI solutions, colocation data centers offer numerous benefits:

• Reliability: With redundant power supplies, backup generators, and multiple network connections, colocation centers ensure that your infrastructure remains online 24/7.
• Scalability: Need more computational power? Colocation centers have the space and resources to grow with your needs, allowing you to add more racks or upgrade hardware easily.
• Security: Advanced security protocols, such as biometric access, surveillance, and firewalls, protect sensitive AI data from unauthorized access.
• Cost Savings: Opting for colocation means businesses can shift from capital expenditures (CapEx) to operational expenses (OpEx), which is often more tax-efficient and budget-friendly.

How Does Colocation Compare to Other Infrastructure Options?

When it comes to hosting infrastructure, businesses often consider three main options: public cloud, private on-premises data centers, and colocation. 

Public clouds provide resources on demand and flexibility, but they can get costly for heavy, long-term AI workloads. Colocation provides predictable costs with better control over hardware. On-premises data centers, which are constructed as internal data centers, provide complete control but come with high infrastructure, maintenance, and personnel costs. Colocation combines the control of on-premises with the cost-efficiency of shared resources. The colocation option strikes a balance, offering the control and customization of private data centers with the scalability and cost savings of the cloud.

What Should AI Companies Look for in a Colocation Provider?

When selecting a colocation partner, AI companies should consider:

• Redundancy and Reliability: Look for facilities that offer redundant power and cooling systems, ensuring uptime and reliability.
• Scalability: Choose providers with ample space and flexibility to accommodate future growth, especially as AI models require more hardware.
• Security: Make sure the provider has robust security protocols in place to protect sensitive AI data.
• Location: Proximity to key markets can reduce latency and improve service quality, which is crucial for time-sensitive AI applications.

How Is Sharon AI Leveraging Colocation for Generative AI?

Sharon AI, a leader in high-performance computing (HPC) and AI services, has recognized the benefits of colocation for its operations. Recently, the company deployed 160 NVIDIA H100 GPUs within NEXTDC’s Tier IV-certified co-location facilities. This expansion significantly enhances Sharon AI’s GPU-as-a-Service (GPUaaS) offerings, allowing the company to meet the growing demand for AI-powered solutions in Australia.

The partnership with NEXTDC isn’t just about hardware—it’s about ensuring top-notch performance and security. These Tier IV facilities, known for their efficiency and 100% uptime, provide Sharon AI with the reliability needed to support its AI customers. With plans to deploy NVIDIA H200 GPUs in early 2025, Sharon AI is positioning itself at the forefront of AI infrastructure.

A New Era of AI Computing

The expansion of Sharon AI’s GPU fleet at NEXTDC’s state-of-the-art facilities marks a significant step forward in the realm of generative AI. By leveraging colocation, Sharon AI is not only enhancing its computational capabilities but also paving the way for more scalable and secure AI services. As the demand for AI solutions continues to rise, colocation data centers will play an increasingly vital role in supporting this digital transformation, driving innovation across industries.

In this rapidly evolving landscape, Sharon AI’s strategic use of colocation underscores its commitment to providing cutting-edge AI infrastructure. As AI technology continues to advance, the future of computing looks brighter than ever.