PlatON 2.0 White Paper: Decentralized Privacy-Preserving AI Network | Part 5: LATs & Milestones

LATs in PlatON

LAT is the native utility token that will capture the value around the trustless coordination of actors within the PlatON network.

Settlement

LATs are used as payment and settlement tokens to pay for online economic activities (e.g. trading services/assets, transferring tokens). Users are required to pay and settle transaction fees, service fees, fees for assets such as data or computing power, etc.

Governance

Give the holders a vote in how the network is run, where developers focus their efforts & when software upgrades should be implemented.

Staking

Token holders will have the ability to stake their tokens in order to provide profitable service to the network (validating transactions, computing, arbitration, providing data and algorithm, data labeling) and be rewarded by the network (e.g. block and staking rewards) or by the users (e.g. transaction fees). Token holders can delegate their tokens to the validators for a share of payouts.

Related Research and Progress

Since 2016, we have set up a high level of research funding for privacy-preserving computation and started to reserve cryptographic talents worldwide. Today, we have a large number of top cryptographic talents, including professors and PhDs from major universities in China and the US.

Our research team has been conducting and publishing exploratory in-depth research in the areas of cryptography, Internet of Things, human intelligence, and economics and governance, and publishing relevant research papers in top conferences or journals.

LEAF: A Faster Secure Search Algorithm via Localization, Extraction, and Reconstruction, In ACM CCS, 2020

We have engineered and applied our research results to privacy-preserving AI and open-sourced the implementation of Rosetta, a privacy-preserving AI framework that brings secure multi-party computation to TensorFlow, enabling data privacy protection during AI model training and prediction in a compatible TensorFlow development interface.

We regularly fund academic research and conferences on cryptography and privacy-preserving computation and collaborate intensively with various projects and research groups.

We have sponsored conferences such as Crypto, Eurocrypt, Asiacrypt, CCS, AsiaCCS, IDASH and many more.
Our participation in the Privacy Computing for Ether — MPC implementation of Proof of Custody in Eth 2.0