We have previously explained the current state of the Artificial Intelligence industry and some of the biggest bottlenecks it’s facing, such as centralized AI model ownership, opaque and duplicated model processing efforts, biased and incomplete data sets, insecure data storage and concerns over data exfiltration, last but not least expensive but much wasted computing processing power.

How does TuringNet plan to reshape AI?

TuringNet was born to enable the advancement of AI models and industry. We are creating world’s first open and trustable AI platform with:

100% accessible AI algorithms and decentralized models (DModels) for commercial usage

Completely AI verifiable and traceable model training/inferencing with transparent goals

Total data ownership and transparent data refinery process

Fair share of rewards to the general public based on participants contributions

This is a revolutionary approach to how the public participates in scalable and collaborative model training and prediction. It will significantly reduce duplicated model training and fully utilizes idle computing resources in a collective manner, at the same ensuring data security.

Our tailored solution specifically for AI

This is achieved by several novel designs on TuringNet’s platform. The new incentivizing Learning Byzantine Fault Tolerance (LBFT) consensus mechanism is world’s first tailor-made consensus for and fully compatible with various AI model training needs. In the full lifecycle of DModels on TuringNet’s platform, there will be a verifier and a confirmer to validate the results after each iteration of training or inferencing, LBFT consensus mechanism then allows them to pass and store the information in order to release a fair amount of rewards to all participants who helped to advance DModels.

To ensure extensibility and scalability of the network, TuringNet is implementing the next generation multi-layered architecture with a mainchain plus multiple subchains. This architecture will empower the network to handle 10,000 transactions per second.

Another novel part of our solution is TuringNet’s Graph Virtual Machine (GVM). The GVM adopts graphs as deep learning models, and allows participants on the network to migrate TensorFlow models, as well as other models from mainstream frameworks, into TuringNet’s platform easily, so that constructions of these AI models will not need to start from scratch.

So how are we incentivizing and making sure participants are happy in our ecosystem?

TuringNet offers a sole cryptocurrency, TNET Token, as a functional utility token that can be consumed in various ways onTuringNet’s platform. Instead of collecting funds through the traditional ICO (Initial Coin Offering) model, where a significant portion of the tokens are pre-mined, then distributed to investors and community, we are taking a bold new approach. Not saying the ICO model doesn’t work well, but the true value of tokens in our ecosystem, should play a critical role to incentivize real users who help to grow our ecosystem in the long term. We want to ensure the massive public receives maximized benefits on our self-governing platform.

Based on all these beliefs, we are introducing a new model — Community Mining Offering (CMO). In this CMO model, users can obtain TNET Tokens through accomplishing a number of simple mining tasks on TuringNet’s platform operated by smart contract. This way, legal and financial risks are both mitigated as users won’t have to put in real money to purchase these tokens, instead they get rewards by providing valuable of work on our platform. In the earlier stage, our aim is to lower the bar for the public to participate and start mining through some light tasks. We are exploring and developing a few different ways that will allow the public to enter our platform and start mining with minimum learning curves.

Our solution will foster a frictionless system and maximize benefits and values to all ecosystem partners and participants in the long term. Please stay tuned for more updates down the road.