Problem Statement

The GPU compute industry faces significant challenges:

  1. Existing infrastructures are often centralized, leading to unfair GPU allocation and data security concerns.

  2. High-end GPUs are in short supply due to rising demand from AI and other applications, forcing consumers to pay high rental costs.

  3. Accessibility issues result in wasted GPU potential, as some providers' powerful GPUs remain idle.

  4. Additionally, data privacy and anonymity are at risk, with centralized control granting access to user data, making these platforms insecure and non-anonymous.

These are some of the primary problems faced by the GPU Compute industry:

  • Centralized & Un-reliable: Most of the available GPU compute infrastructures are centralized and can be manipulated by the owners of these infrastructures. This creates room for an unfair GPU allocation mechanism & unsecure data management where users data could be extracted and utilized with their consent.

  • Limited Availability: Due to the rapid surge in the consumption of Graphics Processing Units World-Wide by Generative AI and other computing applications, there has been a shortage in the supply and availability of high-end GPU’s. This leaves the consumer with no other option other than renting out GPU’s for a higher price.

  • Unaffordable Cost: Due to the unavailability, all the current GPU consumers are left with two options, such as Buy a GPU for a 10x the initial cost or rent out cloud GPU power for a higher cost.

  • Accessibility & Wasted Potential: Another significant problem that the GPU industry possesses with regard to GPU providers is wasted potential. While many people are seeking temporary GPU computing capacity, there are certain GPU vendors/providers whose High-End GPUs remain idle.

  • Data Privacy & Anonymity: Due to the centralized control over these GPU compute infrastructures, Your data are at risk as the providers and owners would have complete access to your data, making it completely insecure & non-anonymous to utilize these platforms.

GPU.Network aims to solve all these problems adhering to its vision.

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