The Upsides & Downsides of Public Cloud for European AI

The rapid evolution of AI capabilities has led technical executive teams across Europe to explore public AI platforms, including OpenAI’s ChatGPT, Microsoft Co-Pilot, AWS Bedrock, and Google Gemini.

While these platforms offer substantial functionality and flexibility, especially for experimentation, they also come with significant structural downsides for AI and data that European businesses leaders must consider and address.

Upsides of Public Cloud for AI

• Public cloud services provide a flexible environment perfect for testing and developing AI models.
• Hardware and software pre-configured for AI development and production.
• Unified consumption model if you’re already utilizing public cloud for other services.

Public Cloud and Public AI services are relatively easy and convenient to utilize for small scale experiments with test data. But when you’re serious about deploying AI with any form of (European) sensitive data, complex compliance, governance and legislation challenges will arise.

Downsides of Public Cloud for AI

Lack of European Sovereignty:

• Public clouds lack the sovereignty required for authentic European data considerations and AI processing, including European location, operations, and ownership.
• GDPR, PII considerations

High Costs:

• Public cloud GPU services are typically 2-3 times more expensive than dedicated alternatives and on-prem.

Inadequate Performance:

• Often, these platforms are relatively slow, utilizing standard servers without specialized high-performance networking or optimized data processing capabilities. Inherent bottlenecks constrain GPU capabilities.

Inadequate Support:

• Technical support is often subpar with AI expertise and human interaction, with long wait times for AI hardware availability in Europe.

Structural Lack of Enterprise GPU platform availability:

• Most Enterprise GPUs are in the US regions, and wait times are long and inconsistent for EU regions.

Corporate Bias in LLM Training:

• The training of language models can be biased towards the interests of the corporations that develop and host them.

NEBUL – The European-Native AI Cloud

For European companies seeking a compliant, cost-effective, and highest-performance AI solution, the Nebul European Private & Sovereign AI Cloud is the answer:

EU Sovereign Data Compliance:

• Adheres to GDPR and other EU data regulations like EU operations, ownership, data governance and compliance for sensitive data types.

NVIDIA-Powered Performance and Support:

• Built on NVIDIA reference architecture, featuring the world’s fastest GPUs (H100s, H200s and B200s)

Cost Efficiency:

• At least 50-75% savings compared to public cloud services, with flat, predictable monthly costs.

Unmatched Speed of processing:

• Provides specialized networking and data storage systems for fastest possible AI processing, which improves time-to-value and reduces costs.

Relentless (Human) Support:

• Ensures immediate availability of AI hardware in Europe with robust onboarding and tech support.

Nebul’s Private Sovereign AI Cloud has been specifically designed for the European AI development and production workloads. Nebul’s European AI Cloud NVIDIA software, hardware and support, considering all European regulations and legislation. Based on the NVIDIA SuperPod reference architecture.

Nebul sets the standard for maximum utilization, efficiency and performance for AI development and inference production in Europe.

Contact us to learn more: hello@nebul.com