DeepBrain Chain Inaugurates the Skynet Project
DeepBrain Chain (DBC) will inaugurate a new project known as Skynet with the aim of developing a decentralized Artificial Intelligence Testnet that will form the base of the upcoming MainNet.
DBC is a blockchain-powered AI platform whose objective is to assist startups in the AI industry to have smooth operability, affordable services, secure transactions, and much more. By activating the Skynet project, DBC has made a significant step towards the realization of its ultimate goal, which is to establish a blockchain platform with the benefits mentioned earlier.
What is the Skynet Project?
For movie enthusiasts, the word ‘Skynet' rekindles memories of the popular 90s' film series known as Terminator. In the movie, Skynet is an AI corporation that is determined to eliminate the human race. Contrariwise, DBC's Skynet project aims to transform the global AI industry positively. Earlier this month (June 2018), the DBC research team successfully launched three machine learning models based on the Testnet of the upcoming blockchain platform. Later on, DBC decided to activate the Skynet project since it is a more significant improvement of the initial testing phase and operates on a global scale.
Typically, the core components of any AI system are algorithms, computer processing power and testing models (prototypes). Of the three, processing power is the most expensive with most businesses spending significant portions of their revenue on computing infrastructure. DeepBrain Chain provides a cheaper alternative that substantially reduces this expenditure by up to 70%.
Besides the mitigation of expenses, DeepBrain Chain also has other benefits. For instance, university and other significant research centers usually act as both consumers and vendors of AI services. As result of differing consumption needs, processing power often goes to waste when the machines are idle. By joining the DBC MainNet, such computers will have privileges such as an increased chance of being consensus nodes, free usage of processing power aggregated from the Testnet computers and much more. Notably, all these perks come at a relatively affordable fee.
Applicability of the DeepBrain Chain Blockchain Platform
In this digital era, the applicability of AI technology covers nearly all facets of human life. Unlike conventional digital currency mining hardware, designated AI computers to have heavy customizations as well as advanced configurations. Their features are incomparable to high-end gaming computers and mining GPUs. To participate in the DBC Testnet campaign as a node, machines have to meet certain bare minimums, among which is an NVidia 1080Ti GPU or higher. During this initiative, DBC intends to recruit 1,000 testing nodes for the Skynet project.
The DBC decentralized blockchain is ideal for individuals or firms that require an AI system that is swift, score and efficient. Furthermore, the distributed ledger will support the issuance of cryptocurrency tokens as well as the deployment of other products. In exchange for their participation, the member nodes will receive DBC tokens paid by the consumers of the computing power. Also, participants can make profits through mining. Ultimately, DBC intends to leverage the global AI community to develop a comprehensive training module that has testing models.
The Importance of Data Security
Given that data security is a crucial aspect for all businesses, DBC prioritizes the safety of its blockchain network. In this regard, the platform has a training task submitter that continually evaluates the progress of training of real-life AI models. Moreover, this feature timestamps all developments on the blockchain deducts earning from malicious nodes and ranks the nodes according to their performance.
Additionally, the DBC platform will assign different levels to training tasks according to their complexity. This prevents nodes from maliciously increasing their overall ranking by completing several low-level tasks. The submitter will also give preference to trusted nodes when allocating high-level tasks.