On 10 December 2021, DeepBrainChain conducted an AMA in the Cryptoscreen Community. Our guest is the Jack Lee of DeepBrainChain.
Lots of questions as usual from the Community about DeepBrainChain progress. The DeepBrainChain team took part in a very interesting AMA session which included introductions, questions from twitter, and a live AMA session with the Cryptoscreen community. If you missed the AMA in person, read this recap for a deeper insight into DeepBrainChain.
Let’s take a look at the most interesting points of our conversation.
Okay, Before I start the first session can you introduce yourself to our community?
Jack_ Lee :
Hello, I’m Lee, I’m glad to have such an opportunity to chat with you, I’ve been working with the Founder Feng for nearly 10 years, we have more than 10 years of entrepreneurial experience in the field of artificial intelligence, we entered the digital currency space in early 2017, we wanted to see how we can combine blockchain technology with artificial intelligence, I am mainly responsible for marketing operations.
thanks for the introduction.
Your experince will certainly motivate us in the future🙂
Okay, In the first session I will give questions about DeepBrainChain, if you have given an answer please say “Done”
Jack_ Lee :
Let’s start first Session
Q1. Can you tell the members a little about DeepBrainChain ?
Jack_ Lee :
DeepBrain Chain was founded in 2017 with the vision of building an infinitely scalable distributed high-performance computing network based on blockchain technology, in order to become the most important computing infrastructure in the era of AI+metaverse. DeepBrain Chain contains three important parts: high-performance computing network, blockchain mainnet and GPU computing mainnet. High-performance computing network officially launched at the end of 2018, blockchain mainnet on May 20th, 2021, after nearly 4 months of public testing, GPU computing mainnet have officially launched last month.
The mainnet of DeepBrain Chain is developed based on PolkaSubstrate, and DeepBrain Chain is also one of the very few high-performance computing projects in the blockchain industry that have achieved large-scale implementation. It has been widely used in various scenarios such as artificial intelligence, driverless vehicles, cloud games, visual rendering, biopharmaceuticals, etc. It has provided high-performance GPU computing power for many enterprises, and cumulatively more than 50 vendors worldwide have deployed high-performance GPU cloud platforms based on DeepBrain Chain network, serving hundreds of enterprises and tens of thousands of AI developer groups. For example, China’s cloud game vendor NetEase Cloud Game uses GPU resources from DeepBrain Chain, China’s leading driverless company AutoX is testing GPU resources from DeepBrain Chain, China’s leading cloud game solution provider TingYu Technology is cooperating with us, Beijing University, Tsinghua University and Harvard University have students and teachers using DeepBrain Chain’s GPUs for AI training.
wow,, this is a very interesting project
Okay, next question
Q2. Can you explain how DeepBrainChain and what kind of services it offers to users?
Jack_ Lee :
It has provided high-performance GPU computing power for many enterprises, and cumulatively more than 50 vendors worldwide have deployed high-performance GPU cloud platforms based on DeepBrain Chain network, serving hundreds of enterprises and tens of thousands of AI developer groups. For example, China’s cloud game vendor NetEase Cloud Game uses GPU resources from DeepBrain Chain, China’s leading driverless company AutoX is testing GPU resources from DeepBrain Chain, China’s leading cloud game solution provider TingYu Technology is cooperating with us, Beijing University, Tsinghua University and Harvard University have students and teachers using DeepBrain Chain’s GPUs for AI training.
Q3. What products does DeepBrainChain have and in the future, will you add more products?
Jack_ Lee :
DeepBrain Chain contains three important parts: high-performance computing network, blockchain mainnet and GPU computing mainnet. High-performance computing network officially launched at the end of 2018, blockchain mainnet on May 20th, 2021, after nearly 4 months of public testing, GPU computing mainnet have officially launched last month.
DBC products have been developed, and no new products will be developed, and many of them will be used to expand the ecology.
Q4. How do you solve liquidity issues and how to ensure user asset security?
Jack_ Lee :
The vision of DeepBrain Chain is to build an infinitely scalable distributed high-performance computing network and become the most important computing infrastructure in the AI+ meta-universe era.
The high performance computing power space is a huge market worth hundreds of billions of dollars and may reach trillions of dollars in the future, and DeepBrain Chain is expected to get a share of it. All the revenue will be used for DBC repurchase and destruction (once the GPU network has more than 5,000 GPU), and DBC is the only payment credential of DeepBrain Chain network, and customers need to use DBC to rent GPUs/add GPUs to the computing pool, which is the basis of DBC value. As long as DBC has more and more application scenarios and requirements, there is no need to worry about liquidity issues.
Regarding the second question，DeepBrain Chain will conduct strict code audit every time it is upgraded, and find professional organizations in the industry to do security audit, and at the same time, it will run for a trial period before upgrading.
Next to the last Question in segment 1
Have you met all your goals in the roadmap till now? And were there any difficulties that you didn’t expect and were not prepared for?
Jack_ Lee :
Jul.2017 The DeepBrain Chain was established, defining the objectives and vision as well as the technical architecture.
Dec. 2017 Fund-raising completed.
Jan.2018 DBC launched on Huobi.pro.
Aug.2018 DBC computing power network goes live and the code is open-sourced on GitHub. (https://github.com/DeepBrainChain)
Nov.2019 DBChain, the first cloud platform based on DeepBrain Chain, goes live. (https://www.dbchain.ai)
Jul.2020 The first DeepBrain Chain-based enterprise cloud platform, Congtu Cloud, goes live. (https://www.congtu.cloud)
Dec.2020 DBChain global AI developer users exceed 10,000, serving more than 500 AI-related universities and labs worldwide.
May 2021 DeepBrain Chain node mainnet officially launched. (https://www.dbcwallet.io)
Jun.2021 DeepBrain Chain mainnet browser goes online. (https://dbc.subscan.io)
Jun.2021 The number of GPU cloud platforms based on DeepBrain Chain exceeds 50.
Jul.2021 DeepBrain Chain GPU computing power mainnet starts public testing.
Aug.2021 Congtu Cloud enterprise customers exceed 100.%
Oct.2021 Total number of GPU computing power in the public test exceeds 1200 cards, and the rental rate is over 98%. (https://galaxyrace.deepbrainchain.org)
Nov.2021 DBC GPU mainnet aunched officially.
As long as we want to do things, we will definitely encounter various difficulties. We are fully prepared for this, and the key is how to solve them when we encounter difficulties.
Thank you for answering all the questions in segment 1 well and very detailed
Okay, we move on to the second session, which is a question from Twitter😊
Jack_ Lee :
QUESTION FROM TWITTER
Marketing is a central element for every project, so that everyone knows the potential that a project can bring is vital to achieve the goals set. What is your strategy to attract new users and Investor to Your platform and keep them long term?
Jack_ Lee :
DeepBrain Chain’s vision is to build an infinitely scalable high-performance distributed computing power network, and become the most important computing infrastructure in the AI+MetaVerse era.At present, DeepBrain Chain is in a leading position in this field. What we have to do is to continuously expand the network GPU scale , And ensure that the GPUs in the network are leased out, and all the income obtained will be used for the repurchase and destruction of DBC (above 5000 cards). All our marketing is to serve this goal.
To attract and retain customers for a long time, the key is to provide competitive products and services, which is also the core competitiveness of DBC.
Next to the second question.
Deep Brain Chain is a AI computing platform powered by blockchain. But most of the users doesn’t understand this. So do you have a tutorial or article on how DBC works? Why do you think AI computing is necessary in blockchain? and can you share key performance indicators of the chain, such as Number of blocks per second, transaction completion time, transaction speed, cost per transaction or something else?
Jack_ Lee :
Humanity is moving into the age of intelligence, and artificial intelligence has been integrated into every aspect of people’s lives. The Artificial intelligence troika: deep models, big data (Internet, sensors, IOT), and high-performance computing (GPU, FPGA, special chips). Individual deep models have an increasing demand for computing power: ImageNet image recognition — 1~10 GPUs, AlphaFold/AlphaFold2 — 100~200 GPUs, BERT language model — 100~200 GPUs, using 1026 TPUs, training time can be shortened to 76min, GPT- 3 language model — 1,000 GPUs OpenAI, 175 billion parameters, training once consumes millions of dollars, multimodal large-scale pre-training model — 2,000 GPUs Beijing Academy of Artificial Intelligence (BAAI). The Artificial intelligence race is the computing power race: solving the problem of computing power supply and demand and rewarding computing power is imminent. DeepBrain Chain hopes to build an infinitely scalable, distributed high-performance computing network through blockchain technology to achieve cost reduction and efficiency improvement of AI computing power worldwide, promote the popularization and democratization of AI computing power, and accelerate the arrival of the era of AI+ metaverse.
DeepBrain Chain contains three important parts: high-performance computing network, blockchain mainnet and GPU computing mainnet. The high-performance computing network was officially launched at the end of 2018, blockchain mainnet was launched on May 20th, 2021, and GPU computing mainnet was launched on November 22nd.
The blockchain mainnet of DeepBrain Chain is developed based on PolkaSubstrate. Except for one block in 30 seconds, everything else changes dynamically; if the network is not congested, it will be packaged in 30 seconds, and 2 blocks will be the most confirmed after packing; the transfer transaction fee, a transfer is currently about 0.00015 DBC.
From the perspective of DBC’s actual business operation, the current performance indicators of the main chain are fully sufficient to support the development of DBC business for a long time in the future.
Hello,, What or who inspires you? It is important for me to know that you live with your project, love it and do everything for it to make it successful.
Jack_ Lee :
We have been focusing on AI projects since 2011, including voice assistants, smart speakers, and other products. We realized the importance of GPU early, but GPU resources are very expensive and many startups can’t afford it. Blockchain technology can help achieve this goal.
We have been committed to this project for four years, and we will continue for at least four more years in the future.
DeepBrainChain is developed based on Polkadot Substrate. How has DeepBrainChain become one of the few high-performance computing projects, which has achieved large-scale implementation in the blockchain industry? How the usability of the computing power network has improved.@blankjout
Jack_ Lee :
DeepBrain Chain network of high-performance computing power is currently mainly only using GPU as the core of high-performance computing resources, in the future we may include NPU/TPU, or even quantum computing; but the current view is that it will be dominated by GPU for quite a long time, the current market value of high-end GPU chip manufacturers Nvidia has nearly three times the market value of CPU chip manufacturers Intel, the reason is that with the development of various emerging industries such as 5G, artificial intelligence, life sciences, autonomous driving, meta-universe, these industries need very powerful computing power, currently GPU is the best choice, but GPU computing power resources are very expensive.
Based on blockchain technology, DeepBrain Chain (DBC) created an infinitely scalable distributed high-performance computing network, the world’s idle GPU resources can independently join the DBC network, customers worldwide can also rent the GPU computing resources of the DBC network, and every transaction data is available on the chain, to promote the popularization and civilianization of AI computing resources, while promoting the blockchain technology on the ground to serve more real industries, it’s not just transactions of monetary value, after more than four years of research and development and commercial operation, this path has proved to be totally feasible.
Last question in segment 2.
I read that DeepBrain Chain’s vision is to build a high-yield distributed scalable computing network. What exactly does a “distributed yield” model mean? What role will users play in this striking model? Does it mean that everyone will be able to get the same benefits equally?
Jack_ Lee :
Due to the development of AI+metaverse technology and the rise of edge computing, the demand for edge-side computing (high performance, high density, low latency, low cost and full coverage) is getting stronger and stronger, and the traditional mega data centers can no longer meet the demand of business development, and it is necessary to schedule and manage data centers of different levels (cloud nodes, metropolitan nodes and edge nodes), so it is urgent that we create an unified distributed computing network to better meet the business demand and at the same time improve the efficiency of computing resources utilization, which is where the advantages of blockchain technology lie.
DeepBrain Chain uses blockchain technology to build a new production relationship and innovatively solve the problem of computing power supply; by reconstructing the cloud computing industry chain, it turns a closed system dominated by giants like cloud computing into an open system where everyone can participate in common construction and share benefits, and jointly build the infrastructure in the era of AI+metaverse.
Welcome everyone to participate in the DBC high-performance computing power ecological construction in a suitable way.
I am interested to invest in your project. When and where can I buy your tokens? Is it already listed exchanges?
Jack Lee :
Does your great project support staking program? If yes. how is your stake system work, what is the requirement for user if they want to stake in your platform?
Jack Lee :
What is your strongest advantage that you think will make your team leading the market?
Jack Lee :
We believe that the profundity of the team’s knowledge of what they are doing largely determines the success or failure of things. We have nearly 10 years of AI experience and naturally have a profound understanding of AI computing, as well as more than 5 years of experience in blockchain technology; it is impossible to do this well by only knowing blockchain or only understanding AI. After the past four years, we have completed all the development goals on the white paper and commercialized many scenarios in the metaverse, autonomous driving, AI, visual rendering, blockchain, etc.
Do you have a Token Burning plan to increase Token value and attract Investors to invest??
Jack Lee :
When the dbc network has more than 5,000 GPUs, the monthly dbc of 800,000 US dollars will be destroyed, if any, the monthly dbc of 8 million US dollars will be destroyed. And the more machines there are, the more dbc pledged. A gpu needs to pledge 100,000 dbc.
Where does the latest technology your project uses come from? Are you afraid that one day your project’s technology will be obsoleted by other projects’ technology if that happens, How will you DeepBrainChaine it?
Jack Lee :
The uniqueness of DeepBrain Chain lies in its being an artificial intelligence public chain, because all the technology research and development is for this positioning, and the main technical innovations are as follows:
Decentralized AI Cloud OS
The underlying technology platform Decentralized AI Cloud OS has all codes as completely self-developed technology;
Responsible for linking computing and storage resources, realizing communication, scheduling and failure recovery among computing resources.
Supporting seamless migration to lightweight IOT devices such as ARM and future migration of computing power to IOT devices.
Building a decentralized AI cloud computing platform based on top of this technology platform.
Completely decentralized AI computation network. ‘’AI Cloud Computation Network’’
One-stop solution, the most optimized AI software platform, supporting all mainstream deep learning frameworks in the industry: TensorFlow, MXNet, PyTorch, Caffe, CNTK, H2O, etc..
Support for multi-AI tasks with parallel start-up execution capability.
Flexible hourly billing model to achieve true on-demand billing.
Open docker computation architecture, second-level deployment and startup, elastic expansion of computing capacity.
The traditional physical GPU server requires a week to install and deploy the application, in the platform it is one-click deployment and one-click to start training, the time is reduced to seconds.
AI docker: Elastic AI Docker computing capabilities, open custom docker image capabilities.
Docker Tech: secure docker enhancement technology.
Ubiquitous decentralized AI computing network: support highly elastic scaling, support massive network system architecture from 10 nodes to 100 million nodes.
Hybrid Multi-Layer Stack Network: a multi-layer network architecture of unstructured, loose P2P peer-to-peer network + structured hybrid P2P network.
Decentralized Virtual Tunnel Network: construction of virtual Layer 2 switching and Layer 3 switching encrypted tunnel network under decentralized network architecture.
Multi-path message routing mechanism.
Efficient compression + scalable self-encoding protocols.
Millisecond-scale peer-to-peer communication infrastructure.
Network support for IPV6 network evolution.
Geo-aware AI inference-based network architecture for more resilient edge computing.
Infinitely scalable decentralized storage network.
Geo-awareness-based distributed storage system.
And the team’s more than ten years of experience in the field of artificial intelligence.
The team’s perception determines the outcome
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