Smarter AI Compute Starts Here: Aethir Brings Distributed GPU Power to GTC

As AI enterprises push the boundaries of innovation, the demand for scalable, cost-efficient GPU infrastructure continues to grow. Many companies are now exploring alternatives to traditional cloud infrastructure, seeking greater flexibility, faster deployment, and lower costs for their AI workloads.

From March 17 to 21, NVIDIA’s GPU Technology Conference (GTC) in San Jose will bring together leading experts in AI, machine learning, and high-performance computing. Aethir’s Chief Technology Officer, Kyle Okamoto, along with members of our growth team, will be on-site to discuss the future of AI infrastructure and how distributed GPU networks are transforming the industry.

Rethinking AI Compute: Aethir’s Distributed GPU Cloud

Aethir was recently recognized by Fast Company as one of the Next Big Things in Tech for its GPU-as-a-Service model, designed to help AI enterprises scale beyond the limitations of hyperscalers. Instead of relying on massive centralized data centers, Aethir operates a globally distributed GPU cloud spanning 95+ countries, providing real-time access to over 400,000 GPU containers, including NVIDIA H100 and H200 GPUs.

Key Advantages of Aethir’s Distributed GPU Infrastructure

1. Faster Deployment: Avoid provisioning delays with on-demand access to enterprise-grade GPUs.
2. Transparent Pricing: No hidden bandwidth fees or unexpected egress charges.
3. Optimized GPU Utilization: Achieve 70%+ GPU efficiency compared to 30-50% utilization in centralized cloud environments.
4. Global Scalability: Reduce latency with infrastructure optimized for high-performance AI workloads.

As AI models continue to grow in complexity, enterprises need flexible, cost-effective, and scalable GPU resources that evolve alongside innovation. Aethir’s GPU-as-a-Service model eliminates the need for upfront capital investments, allowing AI companies to dynamically access the latest NVIDIA GPUs for training and inference at scale.

Aethir’s CTO on the Future of AI Infrastructure

"The future of AI infrastructure isn’t just about raw compute power—it’s about accessibility, efficiency, and adaptability. Aethir’s distributed GPU cloud is designed to provide enterprises with on-demand access to the most powerful AI hardware while eliminating the inefficiencies of legacy cloud models. This shift is critical for industries that require real-time, high-performance AI processing," said Kyle Okamoto, Aethir’s CTO.

Emerging Industries Requiring High-Performance AI Infrastructure

AI-driven innovation is transforming industries worldwide. The demand for high-performance distributed GPU computing is accelerating in key sectors, including:

1. Autonomous Vehicles & Robotics: AI-powered automation relies on large-scale GPU clusters for real-time decision-making and advanced simulations.
2. Pharmaceutical & Biotech: AI-driven drug discovery, protein folding, and precision medicine require significant computational power.
3. Financial Services & High-Frequency Trading: AI models used for risk analysis, fraud detection, and algorithmic trading depend on low-latency, high-speed GPU infrastructure.
4. Media, Entertainment & Gaming: AI-enhanced visual effects, real-time rendering, and cloud gaming demand high-performance, distributed GPU access.
5. Smart Cities & IoT: AI-powered traffic management, security, and energy optimization require scalable, real-time data processing.
6. AI Agents in Enterprise: Enterprises are deploying AI-powered autonomous agents for customer support, sales, operations, and workflow automation, requiring fast, always-available GPU compute to process vast amounts of real-time data.

Aethir’s globally distributed GPU cloud enables real-time AI workloads at scale, providing enterprises with high-performance computing solutions without the CapEx burden.

Flexible AI Deployment with Future-Ready GPU Infrastructure

Aethir’s distributed GPU network is designed to support AI developers, enterprises, and research institutions with bare-metal performance and predictable pricing.

1. Enterprise-Grade GPUs: Access NVIDIA H100, H200, and future GB200 clusters with zero CapEx investment.
2. No Virtualization Overhead: Maximize performance with dedicated GPU access.
3. No Hidden Costs: Eliminate egress fees with predictable, transparent pricing.
4. Rapid Deployment: Launch AI workloads with scalable GPU clusters.

With 20+ global deployment locations, 400,000+ GPUs in operation, and Tier 3 & 4 data centers, Aethir provides the most advanced AI compute infrastructure for enterprises looking to scale their AI models efficiently.

Meet Aethir at NVIDIA GTC

At GTC, Aethir will lead discussions on AI infrastructure trends, distributed cloud solutions, and GPU scalability. Attendees will have the opportunity to learn how AI enterprises can move beyond hyperscaler limitations and adopt a cost-effective, globally distributed GPU compute model.

Connect with Aethir at GTC

If you’re attending NVIDIA GTC and want to explore how distributed GPU cloud computing can optimize your AI workloads, schedule time to speak with the Aethir team. 

For real-time updates, follow Aethir on X (Twitter). To learn more about our AI-first cloud solutions, visit our AI enterprise solutions page.