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DeepBrain Chain Launches Skynet Project - Recruiting AI Computing Power From The Globe

DeepBrain Chain Launches Skynet Project - Recruiting AI Computing Power From The Globe
Snip from https://www.deepbrainchain.org/

DeepBrain Chain (DBC) announced the activation of their Skynet Project, recruiting AI computing power from all over the world. This is a step towards building a globally decentralized AI TestNet to strengthen the foundation for the DBC MainNet.

Most of us must have heard word "Skynet", AI supercomputer from the Hollywood movie, "Terminator"

There are few projects build interest of AI community and DeepBrain Chain is one of those.
On June 3rd, DeepBrain Chain's R&D team has successfully run 3 real-life AI training models on their TestNet for the first time. To assess TestNet's function comprehensively, DeepBrain Chain has activated its Skynet Project to recruit AI computing power from all over the world.

DeepBrain Chain CEO, Yong He, said, "the activation of Skynet Project means that DeepBrain Chain's AI TestNet has entered large scale beta testing. Building on blockchain and decentralized AI computing, DeepBrain Chain will help AI enterprises take off globally, lowering their computing cost, accelerating their products' time to market."

Three crucial elements of AI development are computing power, algorithms and models, each depends on the other. The focus of DeepBrain chain is on the cost of computer power, a huge pain-point for AI enterprises.

DeepBrain Chain helps small and medium size AI enterprises to reduce their cost of buying AI computing power. There are vendors offering AI cloud computing platforms but the cost is still high for small to medium enterprises who want to consume AI computing power. For such small/medium enterprise average cost of AI computing power will be 20% to 30% of their overall funds. This is where Deepbrain chain helps in reducing cost by up to 70%, says the announcement.

In most of the cases, university research centers and AI enterprises are AI computing consumers as well as providers. Based on the needs of computing power, there are times when computing power remains idle. This is where DeepBrain chain brings its benefits to join its blockchain network as computing nodes with onetime small investment. Once joined, there are higher chances of being elected as consensus nodes and use the computing resources from other TestNet nodes on the platform for free.

DeepBrain Chain and its use cases

AI is touching every corner of our lives, from smartphones to driverless cars to face recognition technologies. AI computing power is provided by machines with the configuration at an extremely higher side and generally, these machines are highly customised. To join DeepBrain Chain, these machines must have GPUs with NVIDIA's 1080Ti GPU as their configuration. DeepBrain Chain plans to select 1,000 AI computing machines to be test-nodes for the TestNet.

DeepBrain Chain is building a decentralized AI public chain. It will be offering enterprises or individual with AI needs high-performance computing power and data privacy. AI enterprises can also issue their own token on DeepBrain Chain, deploy their products on the platform.

Deepbrain incentivises AI computing node on their blockchain in two different ways. One, the DBC token that the system rewards them for mining and the second, DBC token paid for by AI computing power consumers. On the foundation of AI public chain, using the unified AI cloud network to build an AI model development and training platform as well as the marketplace is the goal.

DeepBrain Chain's Senior Test Architect & Specialist, Steve Miao said, "compared to our competitors, DeepBrain Chain offers powerful computing power while maintaining a low cost. Enterprises can run their common or optimized AI models, AI data on the platform. DeepBrain Chain's network is faster at creating new blocks and has a shorter reaction time compared to BTC and ETH, offering users different levels of customized security solutions as well. Our comprehensive AI ecosystem and solutions are not seen in other suppliers."

On DeepBrain Chain TestNet, it supports TensorFlow DeepLearning, H2P Machine Learning frameworks. TensorFlow is the industry's most popular AI DeepLearning framework developed by Google, it can be used on image recognition, voice recognition, NLP and other various deep learning fields while H2O is the industry's most popular machine learning and predictive analytics framework. These frameworks have the most AI and machine learning developers in the industry.


Security on DeepBrain Chain

DeepBrain Chain ensures the system's security. For real-life AI training tasks, the AI training task submitter can track the status of the training at all times.

Time of computing and diaries will be recorded. If a computing node behaves maliciously then as a penalty their deposit will be taken away. The DeepBrain Chain system brings in system ranking and user review mechanism, conduct ranking on the result of training.

Also, DeepBrain Chain's AI training tasks have a categorising system, normal level tasks will get computing nodes assigned by the system randomly (to prevent malicious behavior of manually accumulating higher ratings by continuing to run low-level training task to get a good ranking). For high-level tasks, the task submitter can choose nodes they already trust to do part of the training, as well as verifying the result of the training.

Steve Miao said, "in the future, whoever has more powerful computing power will be the terminator in the film, DeepBrain Chain consolidates all computing power to service the industry. Our service perfectly serves NLP, image recognition, voice recognition and other applications in the AI industry."

The announcement said that DeepBrain Chain's TestNet plans to go live at the end of June. After their MainNet goes live in the second half of the year, the R&D team will continue to research the possibility of large-scale AI distributed training and the whole network wise distributed training.

DeepBrain Chain was awarded "Most Outstanding Technology Award" at the Global Blockchain Leaders Summit (GBLS) held in Hangzhou on June 6, 2018,. This is the recognition of DeepBrain Chain innovative business model using blockchain technology, solving the three biggest hurdles, high computing cost, low data security and long product-launching period in the AI industry.

The announcement states below configuration requirements for joining the Skynet Project:

  • GPU with 2, 4, 8 or more GPUs with the configuration of GeForce GTX 1080Ti or above; (to act as AI TestNet computing node)
  • Over 4TB's storage resource; (to act as AI TestNet's storage node)
  • 64G or more of memory;
  • Over 100Mbps bandwidth.

Applications opened on June 15, 2018, and can be applied here: http://cn.mikecrm.com/cR6GyGs



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