Phoenix Oracle Network — Beta Launch!

  • The notion of “data” as an abstract concept that include raw data, structured data, schema, objects, models, and logic. Through our oracles, combined with our focus on decentralized AI, we are able to harness the value and potential of blockchain oracles to a much deeper extent. Phoenix Oracle Network serves as a secure and trusted gateway to facilitate and coordinate off-chain AI computation, privacy-preserving business logic, and key data itself with a on-chain governance. This means that Phoenix Oracle Network is not only a secure gateway for data itself, but also AI models, parameters, logic, and 3rd party data exchange.
  • Most current use cases of blockchain oracles are transactional, or involve the smart contracts being the endpoint of the oracle data request. For example, in cases of DeFi, from an off-chain data source. In the case of Phoenix Global specific use cases, such as Federated learning, the use of the oracle is not limited to data requests (ie. Price lookups) but rather exchange of information, models, and logic between participants of the same dApp as well, not necessarily needing outside data in order to create value. One simple example – the oracle will assist in the synchronizing the parameters of a trained machine learning model across computation nodes, which an iterative process that happens continuously.
  • Enable Phoenix Oracle users to easily access proprietary datasets for enterprise data use cases (AI, marketing, risk management, etc) that are rare and cannot be accessed by other oracle solutions. DataX will enable users to pay using a pay-as-you-go model (using the Phoenix Global token PHB) and the data to be verified via Phoenix Oracle Network (most of these data would require expensive bulk enterprise contracts otherwise). Current data partners include Unionpay, China Telecom, WeChat, and various commodity and economic data vendors.
  • Enable Phoenix Oracle users and federated learning participants to cross-monetize and trade datasets. DataX will also enable participants to “trade” their datasets in a decentralized manner in order to have enriched datasets for machine learning for various use cases, including consumer insights and CRM on a B2B/P2P basis. For example, two enterprises may have different data on the same consumer/customers – DataX will facilitate a decentralized value-weighted exchange of such data, which would ultimately be Oracle-verified and can directly be used in federated learning. This type value exchange would have transformative value.

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