• The partnership will provide scalable, decentralized solutions for cutting-edge AI applications.
  • Consensus techniques are used by Mira’s AI output verification system to drastically reduce errors.
  • The collaboration with io.net will allow Mira to extend its operations while reducing expenses and latency.

The DePIN for GPU compute, io.net , and Mira Network, a provider of trustless AI output verification, have announced a strategic alliance. The partnership will provide scalable, decentralized solutions for cutting-edge AI applications while addressing issues with AI accuracy and dependability.

Consensus techniques are used by Mira’s AI output verification system to drastically reduce errors and provide trustworthy results. By gaining access to decentralized GPU infrastructure, the collaboration with io.net will allow Mira to extend its operations while reducing expenses and latency.

The Node Delegator Program of Mira Network, which is fueled by io.net’s decentralized compute network, will also benefit from the availability of reasonably priced GPUs. In order to assist Mira’s consensus procedures and get network benefits, the project enables contributors to assign GPU resources. For people and organizations interested in decentralized AI, the program reduces the technological obstacles to admission.

Tausif Ahmed, Chief Business Development Officer at io.net, said:

“AI’s full potential can only be realized once it can be fully assured of providing consistent, reliable, and unbiased insights. Through this partnership with Mira Network, we’re not only addressing AI’s accuracy challenges but demonstrating the power of decentralized compute.”

Stone Gettings, Head of Growth at Mira Network, added:

“At Mira, we believe that AI’s vast potential is only just beginning to be discovered and that reliability and trust will be integral to accelerating adoption. As we prepare to launch our Node Delegator Program, the support of io.net will prove invaluable in further decentralizing our network while providing users with access to reliable compute.”

Even though the use of AI is expanding quickly, organizations still encounter some obstacles when using the technology, such as up to 30% AI error rates for tasks requiring advanced reasoning. This is resolved by Mira Network using sophisticated consensus techniques that assess AI-generated outputs across several models, bringing first-pass errors down to 5% and, with further research, aiming for error rates of less than 0.1%.

The worldwide distributed computing network of io.net has enabled Mira to have the reliable and scalable GPU infrastructure needed to support its verification methods. With thousands of GPUs made available by io.net, Mira will be able to accommodate its expanding user base while preserving smooth, low-latency performance.

Mira is using cutting-edge consensus techniques to design the verification layer for AI systems that lack trust. To allow dependable AI execution at scale, the network uses distributed verification protocols and advanced binarization techniques. With more than 200,000 users and many production implementations, Mira is setting new standards for AI dependability via its research and development of LLM consensus and verification systems.

Making AI systems truly autonomous and dependable has advanced significantly thanks to the network’s creative management of compound error rates and verification of intricate reasoning chains.