The premise of cooperation is alignment. The collaboration between @irys_xyz and Allora can be considered a perfect match between data infrastructure and Decentralization AI networks. After all, the core pain points they address through their collaboration are data quality and credibility.

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🔍 The core value lies in data verification
As a Decentralization reasoning network, Allora requires a large amount of reliable data to train and optimize AI models. Traditional AI training often faces issues of opaque data sources and varying quality.

The programmable data chain provided by IRYS perfectly addresses this issue. Each piece of on-chain data comes with complete traceability information and verification mechanisms, ensuring that Allora's AI model can learn based on real, verifiable data.

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⚡️Real-time breakthrough
The multi-ledger architecture of IRYS allows data to quickly propagate from the submission ledger to the release ledger, which is crucial for Allora's self-improvement mechanism.

AI models need to continuously receive new data to optimize their predictive capabilities. IRYS's real-time data processing ability enables Allora to quickly respond to market changes and provide more accurate predictive results.

The data on IRYS can set its own access rules and pricing mechanisms, and Allora's AI services require payment for data according to the rules.

This model allows data creators to benefit directly from AI training, rather than being exploited by the platform as in traditional models.

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IRYS's third-quarter data rose from 73 million to 855 million, a 11.7-fold increase that sufficiently proves the market's demand for programmable data is surging.

The Allora mainnet is about to launch, requiring a large amount of high-quality data to support the operation of its Decentralization AI network.

I personally believe that the significance of this collaboration with @irys_xyz lies in the fact that when data truly becomes programmable and tradable assets, the value distribution logic of the entire AI economy will be redefined.