Businessinsider

January 17, 2022About 7 min

Businessinsider

DeepBrain Chain Computing Power Mainnet Launches Online, Meaning All GPU Servers Can Now Freely Connect to the DBC Network, All Information Available On-Chain

Businessinsider:https://markets.businessinsider.com/news/stocks/deepbrain-chain-computing-power-mainnet-launches-online--meaning-all-gpu-servers-can-now-freely-connect-to-the-dbc-network--all-information-available-on-chain-10855897

Singapore, Singapore--(Newsfile Corp. - December 17, 2021) - With the advent of a digital era represented by Metaverse + AI, high performance computing power will become the most important basic resource. As the most important computing infrastructure in the Web3 world, DeepBrain Chain can strongly improve the problems faced in the field of computing power and empower the digital era.

DeepBrain Chain - Distributed high-performance GPU computing network

DeepBrain Chain was founded in 2017 with the vision of building an infinitely scalable distributed high-performance computing network based on blockchain technology to become the most important computing infrastructure in the era of 5G+AI+metaverse. DeepBrain Chain itself is an open-source GPU computing power pool and GPU cloud platform, which means anyone may become a contributor and user of computing power in DeepBrain Chain. So, whether it is idle GPU computing devices (which meet the requirements of DeepBrain Chain network) or some professional GPU computing providers, they can access the DeepBrain Chain system without restriction and get incentives by providing computing power. As for computing power users, they can get high-quality and cost-friendly computing power services in the DeepBrain Chain system based on DeepBrain Chain's native token, DBC, which constructs a decentralized computing power supply and demand ecosystem.

DeepBrain Chain contains three important parts: the high-performance computing network, the blockchain mainnet and the GPU computing mainnet. The high-performance computing network officially launched at the end of 2018, the blockchain mainnet on May 20th, 2021, after nearly 4 months of public testing, the GPU computing mainnet has officially launched on November 20th .

DeepBrain Chain's main chain is developed based on Polkadot's Substrate framework and is a member of the Polka family. The distributed computing network, on the other hand, is the computing power supply center of DeepBrain Chain and works together with the DeepBrain Chain blockchain network. The computing power user, on the other hand, gets the service through the DeepBrain Chain cloud platform, which can be considered as the client-end. The overall system architecture of DeepBrain Chain is relatively complex, and the computing network it builds has two main advantages: global service capability and strong computing resources.

The launch of DeepBrain Chain GPU computing mainnet means that anyone in the world can freely join the network with GPU resources that meet the requirements of DeepBrain Chain network, and everyone can freely rent GPU resources in DeepBrain Chain network to support their business development, and all transactions are traceable on the chain, realizing complete decentralization.

The Ability to Serve the Globe

Traditional centralized computing platforms may only be able to serve some regional users due to trust factors such as data security, making it difficult to expand their business globally. Likewise, such large centralized computing providers will concentrate their data centers in remote areas with fewer natural disasters, which means they have difficulty in meeting the proximity computing requirements of different territories. In particular, it is difficult to meet the requirements of some application scenarios with high computing requirements, such as autonomous driving.

The computing power of DeepBrain Chain itself is distributed, and the introduction of blockchain technology solves the trust issue well. Through moving the computing power on chain and distributed configuration terminal, DeepBrain Chain as a platform party does not hold the control of any machine. At the same time, the computing resources will be allocated through smart contracts, and any economic-related behaviors (token pledge, resource contribution) will be presented on the chain, and in general, DeepBrain Chain is trustworthy and not affected by geopolitical factors.

As a distributed cloud computing network, the computing power supply of DeepBrain Chain is distributed all over the world, and the computing power supply nodes all over the world can be automatically transformed into metropolitan nodes and edge nodes to meet the nearby computing demands, and even a single point of node failure does not affect the GPU computing power supply, and the system as a whole becomes more fault-tolerant due to the decentralization.

Powerful And Inexpensive High-Performance Computing Resources As Support

At present, mainstream cloud computing service providers usually concentrate their computing power relatively closed in multiple data centers consisting of hundreds of thousands of servers with CPUs as the core, so as to continuously provide computing services to the global network. With the surge in market demand, such cloud providers will further expand their hardware, but the overall price level of computing power is still very expensive.

For example, AI requires huge computing power to run, which requires a large amount of computing power supply. With the GPU computing hardware equipment, the price can be up to hundreds of thousands to millions, and some AI projects such as Alphago, which once beat Go master Lee Sedol, cost hundreds of thousands of dollars for one training model. The cost of expensive computing is also one of the elements that hinder the development of AI.

DeepBrain Chain allows GPU computing servers all over the world to become its nodes, which theoretically has unlimited scalability, and any computing power provider who meets the conditions can become a computing power supply node and gain revenue. For professional GPU computing power providers, these GPU servers are hosted in T3 level or higher IDC server rooms to ensure stability, and on top of that, DBC software is installed into the servers to access the DBC computing power network. Some idle computing power can be connected to the mining pool of DeepBrain Chain to improve GPU utilization and further exchange for extra income. Therefore, in DeepBrain Chain, a large amount of distributed computing power will be gathered, and the cost of computing power will be much lower than the centralized computing power platform, which greatly reduces the cost of GPU computing power acquisition.

Although, the model of DeepBrain Chain and the current mainstream cloud computing platform may be in a competitive relationship, but in fact such mainstream platforms such as Ali cloud and Amazon cloud can access the DBC network as computing nodes and gain revenue, so DeepBrain Chain and these computing suppliers are actually in a competitive but also cooperative relationship.

In a nutshell, computing power enhancement and energy sustainability are both the core constraints and investment opportunities of the meta-universe. The opportunities spawned by the meta-universe will not be limited to GPU, 3D graphics engine, cloud computing and IDC, high-speed wireless communication, Internet and game company platforms, digital twin cities, sustainable energy such as industrial meta-universe solar energy, etc. In particular, the decentralized ecosystem of DeepBrain Chain with a layout in the field of high-performance GPU computing power, while providing high-performance computing resources for the field of science and technology, is positioned in a huge blue ocean market. Of course, with the launch of the mainnet of DeepBrain Chain, all people will be able to participate in it and enjoy the dividends of the meta-universe era.

Empowering Meta-universe and AI

Although DFINITY, which has a higher reputation, also focuses on decentralized computing power market, DFINITY mainly focuses on CPU computing power, while DeepBrain Chain focuses on GPU computing power, which is an important difference between the two.

Both CPUs and GPUs can produce computing power, but CPUs are mainly used for complex logic calculations, while GPUs, as special processors with hundreds or thousands of cores, can perform massively parallel calculations and are more suitable for visual rendering and deep learning algorithms. In contrast, GPUs provide faster and cheaper computing power than CPUs, with GPU computing power often costing as little as one-tenth the cost of a CPU.

At present, GPU computing power has been deeply embedded to artificial intelligence, cloud games, autonomous driving, weather forecasting, cosmic observation, and other scenarios that need high-end computing supply, there is a surge for the demand of GPU power in these high-end industries, the market demand for GPU computing power in the future will be much higher than CPU computing power.

Therefore, DFINITY is mainly dedicated to the blockchainization needs of popular network applications, such as decentralizing information websites and chat software. DeepBrain Chain, on the other hand, is more suitable to serve the needs of high-performance computing, such as artificial intelligence, cloud gaming and deep learning.

The founder of DeepBrain Chain, a veteran AI entrepreneur, has stated that DeepBrain Chain was built in the early days to combine AI with blockchain in order to reduce the cost of the massive computation required for AI. And the total global market for AI-powered hardware and software infrastructure is set to grow to $115.4 billion by 2025.

The artificial intelligence space involves a wide range of fields, and the AI-driven infrastructure accounts for 70% of the total. The current popular technology fields such as autonomous driving, robotics, high-end Internet of Things, etc. are interspersed with AI technology, which means that DeepBrain Chain will further drive the development of the whole technology field by empowering the AI segment. At present, the computing power required for AI doubles every 2 months, and the supply level of the new computing power infrastructure carrying AI will directly affect the AI innovation iteration and industrial AI application landing. The high-performance computing and AI industry driven by GPU power will grow exponentially in the next few years.

At present, some AI research fields quite favor the services provided by the DeepBrain Chain system. It is understood that from 2019 to date, DeepBrain Chain AI developer users come from 500+ universities in China and abroad. Many universities that offer AI majors have teachers or students who are using the GPU computing network of DeepBrain Chain, and the application scenarios cover cloud games, artificial intelligence, autonomous driving, blockchain, visual rendering, and the AI developer users based on DeepBrain Chain have exceeded 20,000. At present, more than 50 GPU cloud platforms, including Congtu.cloud, 1024lab and Deepshare.net, have been built on the DeepBrain Chain network, and the enterprise customers served by DeepBrain Chain have exceeded hundreds.

A meta-verse is a virtual ecosystem that is very complex and needs a lot of computing power to support. For example, the construction of a large number of 3D scenes requires large-scale rendering; for example, in the metaverse, multi-person interaction in the same space requires more algorithmic support, such as multi-person voice interaction in some multi-person scenes involving distance and proximity, dynamic capture and real-time rendering of many users' mutual actions, and the resulting high rendering and low latency requirements caused by the massive amount of computing. In addition, the open meta-universe ecosystem, UGC (user-generated content) built by a large number of users all need the support of a large number of operations or a large number of AI scenes, etc.

Large models of artificial intelligence will serve as the brains of the ecosystem operation of the meta-universe. AI utilizes advanced data, tensor and pipeline parallelization techniques that enable the training of large language models to be efficiently distributed across thousands of GPUs, and it is evident that the construction of the meta-universe is deeply dependent on the development of AI technology.

With the convergence of 5G+AIOT and the advent of the meta-universe era, the global computing industry is entering the era of high-performance computing + edge intelligence, and the massive, real-time distributed high-performance cheap GPU computing power provided by the DeepBrain Chain network has become the most important computing infrastructure in the AI+meta-universe era.

In a word, the distributed GPU computing power ecosystem built by DeepBrain Chain will help break through the bottleneck faced by the computing field nowadays, accelerate the coming of the digital era, and become one of the most important infrastructures in the Web3.0 world.

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