PlatON
As an underlying public chain, PlatON has demonstrated comparable strength to mainstream public chains such as Ethereum, Eos, Cosmos, Polkadot, Algorand, Dfinity, Solana, Near, etc. in terms of decentralization, security, performance, and smart contract development. However, unlike these public chains that primarily aim to build WEB3 network infrastructure and decentralized application platforms, PlatON focuses on building privacy preserving computing networks and artificial intelligence collaboration networks.
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Privacy protection technology:
Privacy Protection Based on Cryptography: PlatON adopts cryptographic based secure multi-party computation (MPC) technology and advanced privacy protection algorithms such as homomorphic encryption (HE), which provide a higher level of data privacy protection compared to traditional TEE (Trusted Execution Environment) technology. This technological approach enables PlatON to ensure data confidentiality and privacy while ensuring calculation accuracy. -
Efficient off chain computing model:
Verifiable Computing (VC): PlatON migrates heavy computing tasks off chain through verifiable computing, thereby reducing the computational burden on chain and improving overall performance. After the off chain computation is completed, the correctness of the results is ensured through verifiable calculations, achieving infinite expansion of computing power and efficient computation verification. -
Powerful scalability and high performance:
Second layer protocol and sharding technology: PlatON significantly improves the scalability of blockchain by extending the second layer protocol and using sharding technology. Sharding technology enables PlatON to form a blockchain system consisting of a main chain and multiple application chains, with each application chain focusing on specific types of services, thereby improving overall performance and efficiency.
Efficient consensus protocol: PlatON’s unique Giskard consensus protocol, combined with VRF and probability distribution random selection of validators, achieves decentralization while maintaining low network bandwidth requirements and good TPS (transactions per second) performance. -
Focus on artificial intelligence collaboration:
① AI model privacy training and agent construction: PlatON focuses more on privacy training of AI models and the construction of AI agents. It supports efficient training of AI models while protecting privacy, and promotes interoperability between AI agents, providing strong support for the sustainable development of artificial intelligence.
② Dedicated privacy computing acceleration hardware: PlatON plans to provide dedicated privacy computing acceleration hardware for AI, which will further enhance the efficiency and performance of privacy computing and provide more solid underlying support for artificial intelligence applications. -
Rich application scenarios:
Wide application areas: PlatON’s technology application scenarios have expanded to multiple fields such as healthcare, credit reporting, advertising, AI, IoT, payment settlement, key management, etc. The widespread application in these fields proves the practicality and value of PlatON technology. -
Open ecology and community support:
Open financial infrastructure: PlatON, as an open financial infrastructure, has attracted numerous developers and partners to join. By building an open ecosystem and strong community support, Platon is able to continuously drive technological innovation and application development.
The core focus of the PlatON project is the integration of privacy computing and artificial intelligence. Compared with public blockchain projects with privacy computing features such as Enigma, Oasis, and Phala, PlatON adopts a unique privacy technology roadmap. It is based on cryptographic secure multi-party computation technology, rather than TEE technology, which gives PlatON a unique advantage in privacy protection. Meanwhile, as an independent and complete blockchain network, Platon’s independence and completeness also provide strong guarantees for the stability and reliability of the project.
In terms of privacy computing, PlatON not only supports basic privacy protection requirements, but also handles more complex machine learning privacy computing. This means that on PlatON, developers can handle and analyze privacy data more flexibly without worrying about data leakage or abuse. In addition, Platon will also provide dedicated privacy computing acceleration hardware for AI to further improve the efficiency and performance of privacy computing.
In addition to privacy computing, PlatON also focuses more on privacy training of AI models and construction of AI agents. Through PlatON, developers can train and optimize AI models while protecting privacy, thereby improving the accuracy and efficiency of the models. Meanwhile, Platon also supports the interoperability of AI agents, which enables smoother interaction and collaboration between different AI agents, thus forming a more collaborative and efficient AI ecosystem.