Cost Efficient On-Premises AI Processing with Phison aiDAPTIV+
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Mitch Lewis
The emergence of generative AI presents significant opportunities for innovation across organizations of all sizes and industries. However, the technical infrastructure required for both model fine-tuning and inference often poses a major challenge due to the reliance on expensive, high-performance GPUs. This paper examines the cost and data privacy limitations associated with traditional cloud and on-premises approaches and explores how Phison aiDAPTIV+ can help organizations overcome these barriers. Through hands-on testing, Signal65 validated the solution’s capabilities and assessed its impact on easing AI infrastructure challenges.
Key findings include:
- Successful fine-tuning of four distinct AI models under conditions where standard configurations failed due to memory constraints
- Fine-tuning of a 70-billion-parameter AI model on a single GPU with only 48 GB of VRAM when enabled by the aiDAPTIV+ GPU memory extension
- Up to 85% cost savings compared to traditional AI infrastructure deployment approaches
- Simplified AI development, enhanced data security, and improved inference performance
Research commissioned by:
