Ethereum parity32 bit
Publish: 2021-05-12 03:47:48
1. Ethereum also uses blockchain technology, but it is more convenient to use than bitcoin's blockchain Turing, which is complete and open source. Anyone can create their own application on the basis of Ethereum
2. It's a long story about the difference between 32-bit and 64 bit systems. First of all, let's understand the architecture technology of CPU. Usually we can see that there are x86 and x64 marks on computer hardware. In fact, these are two different CPU hardware architectures. X86 stands for 32-bit operating system and x64 stands for 64 bit operating system. So what does the "bit" in 32-bit and 64 bit mean? Compared with 32-bit technology, this bit of 64 bit technology means that the data width of cpugprs (general purpose registers) is 64 bits. The 64 bit instruction set is the instruction that runs 64 bit data, that is, the processor can run 64 bit data at a time. Let's take a simple but not particularly accurate example: the 32-bit throughput is 1m, while the 64 bit throughput is 2m< First, download a ghost version of win7 operating system, and now Doudou takes "deep technology ghost win7 SP1 x64 computer city installed version v2013.10" as a demonstration.
3. There are many kinds of digital asset wallets. I'll try to make it as simple as possible
according to whether to run the whole node, it can be divided into full node wallet and light wallet. The full node wallet refers to the wallet that synchronizes all the blockchain data, while the light wallet only retains part of the data related to itself. We usually use the light wallet
according to whether the wallet is connected to the Internet, it can be divided into hot wallet and cold wallet. Hot wallets are wallets that stay online, also known as online wallets. A cold wallet is a wallet that is not connected to the Internet, also known as an offline wallet. It is usually a computer, hard disk or paper with a private key written on it that is not connected to the Internet. Generally speaking, a cold wallet is more secure than a hot one because it is not connected to the Internet and the private key can hardly be stolen
according to the different ways of private key storage, wallet can be divided into decentralized wallet and centralized wallet. Decentralized wallet means that the private key is not stored and managed by a third party, but generated and managed by users themselves. If the private key is lost, it will not be retrieved. The storage of the private key of the centralized wallet is managed by the platform. Users log in with their accounts, and the exchange wallet belongs to this category
at present, the well-known wallets on the market include Bitian, imtoken, Galaxy wallet, Cobo wallet, etc.
according to whether to run the whole node, it can be divided into full node wallet and light wallet. The full node wallet refers to the wallet that synchronizes all the blockchain data, while the light wallet only retains part of the data related to itself. We usually use the light wallet
according to whether the wallet is connected to the Internet, it can be divided into hot wallet and cold wallet. Hot wallets are wallets that stay online, also known as online wallets. A cold wallet is a wallet that is not connected to the Internet, also known as an offline wallet. It is usually a computer, hard disk or paper with a private key written on it that is not connected to the Internet. Generally speaking, a cold wallet is more secure than a hot one because it is not connected to the Internet and the private key can hardly be stolen
according to the different ways of private key storage, wallet can be divided into decentralized wallet and centralized wallet. Decentralized wallet means that the private key is not stored and managed by a third party, but generated and managed by users themselves. If the private key is lost, it will not be retrieved. The storage of the private key of the centralized wallet is managed by the platform. Users log in with their accounts, and the exchange wallet belongs to this category
at present, the well-known wallets on the market include Bitian, imtoken, Galaxy wallet, Cobo wallet, etc.
4. [interpretation of new technology of auto home]? What is the most important component of the automatic driving system? Is it a sensor? Is it control software? Or processing chip? Personally, I think at the present stage, the processing chip is the most critical component, and its performance directly affects the quality of the automatic driving system. In the past, the top chip technology has been monopolized by foreign enterprises, but with the rapid catch-up of Chinese chip enterprises in recent years, the situation has changed. Today, let's talk about the level of China's automatic driving chip
● what is the autopilot chip for
although L3 level conditional autonomous vehicles have not yet landed in China, from some vehicles with high-level L2 driving assistance system, we can find that these vehicles are equipped with a large number of sensors to detect obstacles around the vehicle, so as to provide data support for control system decision-making. These sensors include millimeter wave radar, ultrasonic radar, camera and so on. These sensors will generate several GB (1GB = 1024MB = 10242kb) of data per second. The autopilot chip needs to process these data smoothly to ensure that the system can make correct decisions in time, so as to ensure the driving safety of the vehicle
maybe you don't have the concept of gigabytes per second. Here's an example from life. The peak reading speed of a common USB 3.0 interface U disk is close to 200MB / s. It takes about 5 seconds to read 1GB files from this U disk, which shows that the amount of data in GB / S is quite large
automatic driving system needs not only to solve the problem of large flow data transmission, but also to solve the problem of how to deal with these huge amounts of data quickly, and the powerful automatic driving chip is the right key.
● what is the level of foreign autopilot chips
although this article mainly talks about the development of China's autopilot chip, we should know ourselves well and win every battle. Before we examine the local situation, we should first understand the situation abroad. There are only three foreign autopilot chips that can really enter the mass proction car market on a large scale: NVIDIA, Mobileye (now acquired by Intel) and Tesla
among them, Mobileye, which takes a practical route, currently has a market share of more than 70%. The procts on the market are mainly eyeq3 chips (0.256tops, "tops" means trillions of operations per second), which are used in L2 driving assistance system, Unless otherwise specified, the computing power indicated in this paper refers to 8-bit integer computing power) and eyeq4 chip (computing power 2.5tops) with L3 level automatic driving ability. For example, Xiaopeng G3, Weilai ES6 / es8 and GAC new energy aion LX adopt eyeq4 chip as the core of their driving assistance system
compared with the computing power of drive PX Pegasus 320tops, the flagship of NVIDIA's previous generation automatic driving platform, the flagship configuration of the new drive AgX Orin platform has achieved multiple performance growth. In addition, the degree of flexibility of the drive AgX Orin platform is further improved compared with the previous platform, which can meet the requirements of different levels of vehicles from general driving assistance to L5 level fully automatic driving through the increase or decrease of hardware configuration
Tesla autopilot 1.0 system uses one NVIDIA tegra3 chip and one Mobileye eyeq3 chip; Autopilot 2.0 system uses one NVIDIA Tegra Parker chip and one Pascal architecture GPU chip; Autopilot 2.5 system uses two NVIDIA Tegra Parker chips and one Pascal architecture GPU chip
the self-developed FSD chip has been carried on the latest off-line Tesla models. The computing power of a single chip is 72tops. The full self driving computer integrates two FSD chips that work independently. One "hangs" and the other "goes up" immediately, which improves the security and stability of the whole system
of course, in addition to the above three enterprises, there are also many enterprises coveting the cake of autonomous driving chips, including Qualcomm, Xilinx, NXP, etc., but the autonomous driving chips that these enterprises are really going to mass proce cars are not large-scale. Limited to space, I will not introce them here
● the rapid rise of China's automatic driving chip Enterprises. Auto driving chip market is booming, and foreign technology giants rush to land. How about the strength of Chinese enterprises? Now let's take a look< The Cambrian China Science and Technology Co., Ltd. (hereinafter referred to as "Cambrian") is a research group led by Chen Yunji and Chen Tianshi under the Institute of computing technology, Chinese Academy of Sciences. The research group began to study neural network algorithm and chip in 2008, and began to publish research results in 2012
in 2016, diannaoyu, the instruction set of deep learning processor proposed by the above research group, was accepted by isca2016. Experiments show that the chip with this instruction set has two orders of magnitude performance advantages in neural network computing compared with the chip with traditional x86 instruction set. As the research results of the research group tend to mature, China Science and technology Cambrian science and Technology Co., Ltd. was officially established, and began to transform its chip and instruction set to the commercial field. Also in 2016, Cambrian released its first commercial deep learning processor, Cambrian 1a
after talking about the company's life experience, let's take a look at its procts. At present, there are two latest AI chip IP licenses in Cambrian, namely cambrian-1m and cambrian-1h. Cambricon-1m-4k, with the strongest performance index, has 8tops computing power at 1GHz clock frequency; Cambricon-1h8mini, with the weakest performance index, has 0.5tops computing power at 1GHz clock frequency. The detailed force calculation parameters of all models can be seen in the table below
cambricon-1m and cambricon-1h are defined as terminal intelligent processor IP. The applications such as face recognition, fingerprint recognition, obstacle recognition, road sign recognition and so on, which appear on mobile phones or cars, can be accelerated by integrating the above processor IP in the chip
the word "edge" mentioned above comes from "edge computing". Edge computing refers to providing network, storage, computing, application and other capabilities at the end close to intelligent devices (terminals) or data sources (cloud), so as to achieve faster network service response and more secure local data transmission. Edge computing can meet the requirements of real-time business, intelligent applications, security and privacy protection, and provide local intelligent services for users. Siyuan 220 plays the role of improving data security, recing processing delay and optimizing bandwidth utilization in edge computing
at present, Cambrian high computing power chip procts are defined as smart accelerators, which can be used to accelerate AI operations in servers. I believe you've heard that Google's alphago AI robot beat South Korea's world go champion Li Shishi. Behind the alphago AI robot is Google's self-developed TPU chip. The features and applications of Cambrian high computing power chip procts are similar to Google TPU. Of course, they can also be regarded as competitors
the difference is that Siyuan 270-s4 adopts a passive cooling design, with a maximum thermal design power consumption of 70W, and is positioned as a data center accelerator card with higher energy efficiency than that designed by artificial intelligence reasoning. This also means that the card will have a "power wall" setting, that is, when the power consumption of the accelerator card reaches the upper limit of the threshold, the computing power will be reced to ensure lower power consumption and heating
Siyuan 270-f4 is equivalent to "full blood version" Siyuan 270-s4, with a maximum thermal design power consumption of 150W and active cooling by turbofan. Good heat dissipation and sufficient power supply enable Siyuan 270-f4 to give full play to the full performance of Siyuan 270 chip. The positioning of the card is to provide data center level AI computing power for desktop environment. In short, it is a high-performance AI accelerator card for desktop
although Siyuan 270 only uses TSMC's 16nm process, the overall energy consumption ratio is quite good. Although the computing power of a single card is less than that of the latest NVIDIA flagship computing card, the peak computing power of five Siyuan 270-s4 / Siyuan 270-f4 parallel cards can also reach the level of NVIDIA A100. However, the more advanced process of NVIDIA A100 should have certain advantages in energy consumption
among them, Siyuan 100-c is equipped with video and image decoding units and adopts passive cooling mode, with the maximum thermal design power consumption of 110W; Siyuan 100-d is not equipped with video and image decoding unit, and adopts passive cooling mode, with the maximum thermal design power consumption of 75W. At present, Siyuan 100 series procts have been applied in didi cloud and Jinshan cloud in 2019. Didi cloud uses Siyuan 100 card to accelerate the elastic reasoning service, which is used for deep learning reasoning task; Jinshanyun uses Siyuan 100 card to accelerate the application of artificial intelligence such as voice, image and video
what I mentioned above is all about server level computing cards. Does this deviate from the topic of autopilot chip that we should talk about? Not really. As mentioned earlier, Cambrian is currently an enterprise focusing on the development of artificial intelligence chips, and the field of automatic driving is not deeply involved, but there are still some achievements through the cooperation with other domestic partners< The br / > WiseADCU CN1 automatic driving domain controller provides the computing power and the number of sensor connections required for L3 or above level automatic driving system, and realizes the self control of seven key control points of simulation, model, system, architecture, encoding, acceleration, and algorithm.
in fact, e to the weak performance competitiveness of processor procts, Weisheng group has long withdrawn from the competition in the mainstream x86 processor market, leaving Intel and AMD competing in the market. Since the establishment of megacore, it has mastered Viagra's x86 technology, made comprehensive improvement and Optimization on the basis of the latest processor architecture of Viagra at that time, and successively launched zx-a, zx-c, zx-c + and other processor procts
on June 2, the municipal Party committee of science and Technology Innovation Board announced the results of the 33rd review meeting in 2020, and the listing of Cambrian was approved. From acceptance to approval, it took only 68 days for Cambrian to refresh the review speed of science and technology innovation board. Cambrian has become the only AI chip company in A-share market since its listing. The market space in this field is expected to exceed 50 billion US dollars in 2022, with huge development potential. Can Cambrian, which has opened up A-share financing channels, further develop and grow with its unique technical advantages? No one can say for sure, but it is certain that the successful listing of the Cambrian period has won the confidence and hope of many companies engaged in this field, which may usher in the era of Chinese artificial intelligence chips
> horizon robot
OK, after talking about the Cambrian, let's talk about another AI chip enterprise, horizon robot technology research and Development Co., Ltd. (hereinafter referred to as "Horizon"). Horizon is a company founded in 2015 by Yu Kai, former executive vice president of the online Deep Learning Institute, focusing on automatic driving and artificial intelligence chips. Yu Kai is also the originator of Internet autopilot
the horizon established by Yu Kai has always adhered to the direction of combining software and hardware. He believes that algorithms, chips and cloud computing will constitute the three core fulcrums of automatic driving. Compared with the Cambrian period, which focused on building high-performance hardware chips, horizon's business model focused on "algorithm + chip"
● what is the autopilot chip for
although L3 level conditional autonomous vehicles have not yet landed in China, from some vehicles with high-level L2 driving assistance system, we can find that these vehicles are equipped with a large number of sensors to detect obstacles around the vehicle, so as to provide data support for control system decision-making. These sensors include millimeter wave radar, ultrasonic radar, camera and so on. These sensors will generate several GB (1GB = 1024MB = 10242kb) of data per second. The autopilot chip needs to process these data smoothly to ensure that the system can make correct decisions in time, so as to ensure the driving safety of the vehicle
maybe you don't have the concept of gigabytes per second. Here's an example from life. The peak reading speed of a common USB 3.0 interface U disk is close to 200MB / s. It takes about 5 seconds to read 1GB files from this U disk, which shows that the amount of data in GB / S is quite large
automatic driving system needs not only to solve the problem of large flow data transmission, but also to solve the problem of how to deal with these huge amounts of data quickly, and the powerful automatic driving chip is the right key.
● what is the level of foreign autopilot chips
although this article mainly talks about the development of China's autopilot chip, we should know ourselves well and win every battle. Before we examine the local situation, we should first understand the situation abroad. There are only three foreign autopilot chips that can really enter the mass proction car market on a large scale: NVIDIA, Mobileye (now acquired by Intel) and Tesla
among them, Mobileye, which takes a practical route, currently has a market share of more than 70%. The procts on the market are mainly eyeq3 chips (0.256tops, "tops" means trillions of operations per second), which are used in L2 driving assistance system, Unless otherwise specified, the computing power indicated in this paper refers to 8-bit integer computing power) and eyeq4 chip (computing power 2.5tops) with L3 level automatic driving ability. For example, Xiaopeng G3, Weilai ES6 / es8 and GAC new energy aion LX adopt eyeq4 chip as the core of their driving assistance system
compared with the computing power of drive PX Pegasus 320tops, the flagship of NVIDIA's previous generation automatic driving platform, the flagship configuration of the new drive AgX Orin platform has achieved multiple performance growth. In addition, the degree of flexibility of the drive AgX Orin platform is further improved compared with the previous platform, which can meet the requirements of different levels of vehicles from general driving assistance to L5 level fully automatic driving through the increase or decrease of hardware configuration
Tesla autopilot 1.0 system uses one NVIDIA tegra3 chip and one Mobileye eyeq3 chip; Autopilot 2.0 system uses one NVIDIA Tegra Parker chip and one Pascal architecture GPU chip; Autopilot 2.5 system uses two NVIDIA Tegra Parker chips and one Pascal architecture GPU chip
the self-developed FSD chip has been carried on the latest off-line Tesla models. The computing power of a single chip is 72tops. The full self driving computer integrates two FSD chips that work independently. One "hangs" and the other "goes up" immediately, which improves the security and stability of the whole system
of course, in addition to the above three enterprises, there are also many enterprises coveting the cake of autonomous driving chips, including Qualcomm, Xilinx, NXP, etc., but the autonomous driving chips that these enterprises are really going to mass proce cars are not large-scale. Limited to space, I will not introce them here
● the rapid rise of China's automatic driving chip Enterprises. Auto driving chip market is booming, and foreign technology giants rush to land. How about the strength of Chinese enterprises? Now let's take a look< The Cambrian China Science and Technology Co., Ltd. (hereinafter referred to as "Cambrian") is a research group led by Chen Yunji and Chen Tianshi under the Institute of computing technology, Chinese Academy of Sciences. The research group began to study neural network algorithm and chip in 2008, and began to publish research results in 2012
in 2016, diannaoyu, the instruction set of deep learning processor proposed by the above research group, was accepted by isca2016. Experiments show that the chip with this instruction set has two orders of magnitude performance advantages in neural network computing compared with the chip with traditional x86 instruction set. As the research results of the research group tend to mature, China Science and technology Cambrian science and Technology Co., Ltd. was officially established, and began to transform its chip and instruction set to the commercial field. Also in 2016, Cambrian released its first commercial deep learning processor, Cambrian 1a
after talking about the company's life experience, let's take a look at its procts. At present, there are two latest AI chip IP licenses in Cambrian, namely cambrian-1m and cambrian-1h. Cambricon-1m-4k, with the strongest performance index, has 8tops computing power at 1GHz clock frequency; Cambricon-1h8mini, with the weakest performance index, has 0.5tops computing power at 1GHz clock frequency. The detailed force calculation parameters of all models can be seen in the table below
cambricon-1m and cambricon-1h are defined as terminal intelligent processor IP. The applications such as face recognition, fingerprint recognition, obstacle recognition, road sign recognition and so on, which appear on mobile phones or cars, can be accelerated by integrating the above processor IP in the chip
the word "edge" mentioned above comes from "edge computing". Edge computing refers to providing network, storage, computing, application and other capabilities at the end close to intelligent devices (terminals) or data sources (cloud), so as to achieve faster network service response and more secure local data transmission. Edge computing can meet the requirements of real-time business, intelligent applications, security and privacy protection, and provide local intelligent services for users. Siyuan 220 plays the role of improving data security, recing processing delay and optimizing bandwidth utilization in edge computing
at present, Cambrian high computing power chip procts are defined as smart accelerators, which can be used to accelerate AI operations in servers. I believe you've heard that Google's alphago AI robot beat South Korea's world go champion Li Shishi. Behind the alphago AI robot is Google's self-developed TPU chip. The features and applications of Cambrian high computing power chip procts are similar to Google TPU. Of course, they can also be regarded as competitors
the difference is that Siyuan 270-s4 adopts a passive cooling design, with a maximum thermal design power consumption of 70W, and is positioned as a data center accelerator card with higher energy efficiency than that designed by artificial intelligence reasoning. This also means that the card will have a "power wall" setting, that is, when the power consumption of the accelerator card reaches the upper limit of the threshold, the computing power will be reced to ensure lower power consumption and heating
Siyuan 270-f4 is equivalent to "full blood version" Siyuan 270-s4, with a maximum thermal design power consumption of 150W and active cooling by turbofan. Good heat dissipation and sufficient power supply enable Siyuan 270-f4 to give full play to the full performance of Siyuan 270 chip. The positioning of the card is to provide data center level AI computing power for desktop environment. In short, it is a high-performance AI accelerator card for desktop
although Siyuan 270 only uses TSMC's 16nm process, the overall energy consumption ratio is quite good. Although the computing power of a single card is less than that of the latest NVIDIA flagship computing card, the peak computing power of five Siyuan 270-s4 / Siyuan 270-f4 parallel cards can also reach the level of NVIDIA A100. However, the more advanced process of NVIDIA A100 should have certain advantages in energy consumption
among them, Siyuan 100-c is equipped with video and image decoding units and adopts passive cooling mode, with the maximum thermal design power consumption of 110W; Siyuan 100-d is not equipped with video and image decoding unit, and adopts passive cooling mode, with the maximum thermal design power consumption of 75W. At present, Siyuan 100 series procts have been applied in didi cloud and Jinshan cloud in 2019. Didi cloud uses Siyuan 100 card to accelerate the elastic reasoning service, which is used for deep learning reasoning task; Jinshanyun uses Siyuan 100 card to accelerate the application of artificial intelligence such as voice, image and video
what I mentioned above is all about server level computing cards. Does this deviate from the topic of autopilot chip that we should talk about? Not really. As mentioned earlier, Cambrian is currently an enterprise focusing on the development of artificial intelligence chips, and the field of automatic driving is not deeply involved, but there are still some achievements through the cooperation with other domestic partners< The br / > WiseADCU CN1 automatic driving domain controller provides the computing power and the number of sensor connections required for L3 or above level automatic driving system, and realizes the self control of seven key control points of simulation, model, system, architecture, encoding, acceleration, and algorithm.
in fact, e to the weak performance competitiveness of processor procts, Weisheng group has long withdrawn from the competition in the mainstream x86 processor market, leaving Intel and AMD competing in the market. Since the establishment of megacore, it has mastered Viagra's x86 technology, made comprehensive improvement and Optimization on the basis of the latest processor architecture of Viagra at that time, and successively launched zx-a, zx-c, zx-c + and other processor procts
on June 2, the municipal Party committee of science and Technology Innovation Board announced the results of the 33rd review meeting in 2020, and the listing of Cambrian was approved. From acceptance to approval, it took only 68 days for Cambrian to refresh the review speed of science and technology innovation board. Cambrian has become the only AI chip company in A-share market since its listing. The market space in this field is expected to exceed 50 billion US dollars in 2022, with huge development potential. Can Cambrian, which has opened up A-share financing channels, further develop and grow with its unique technical advantages? No one can say for sure, but it is certain that the successful listing of the Cambrian period has won the confidence and hope of many companies engaged in this field, which may usher in the era of Chinese artificial intelligence chips
> horizon robot
OK, after talking about the Cambrian, let's talk about another AI chip enterprise, horizon robot technology research and Development Co., Ltd. (hereinafter referred to as "Horizon"). Horizon is a company founded in 2015 by Yu Kai, former executive vice president of the online Deep Learning Institute, focusing on automatic driving and artificial intelligence chips. Yu Kai is also the originator of Internet autopilot
the horizon established by Yu Kai has always adhered to the direction of combining software and hardware. He believes that algorithms, chips and cloud computing will constitute the three core fulcrums of automatic driving. Compared with the Cambrian period, which focused on building high-performance hardware chips, horizon's business model focused on "algorithm + chip"
5.
More and more people want to steal money by attacking smart contracts. They are taking advantage of the loopholes when smart contracts are combined
in 2020, the total amount of embezzlement or theft in the attack on defi has reached 36 million US dollars. But because dforce attackers returned the stolen $25 million, the actual amount was about $11 million
compared with the early days of Ethereum, the average loss value of each hacker attack has decreased significantly. Eight of the 10 attacks in 2020 are worth less than $1 million
defi
in the early days of Ethereum, most attacks were based on finding indivial vulnerabilities, which enabled attackers to freeze or exhaust smart contracts. This was the case with the notorious Dao hacking incident in 2016, in which $160 million eth was stolen and Ethereum finally forked out. Similarly, the multi signature attack of parity in 2017 caused hackers to steal $30 million, and $150 million in parity's wallet was frozen, all of which were the consequences of such vulnerabilities
the loopholes of such smart contracts are still exploited from time to time. Recently, an attacker succeeded in stealing all Veth from token contracts, making a profit of $900000 just by exhausting the veth-eth uniswap pool. But this is a simple mistake caused by Veth, because there is a logical error in the way Veth modifies the erc20 token standard
generally speaking, the security has been improved, especially for the projects with high attention. Their security improvement is driven by the user's expectation of audit and the improvement of testing tools. Recently, the biggest security problem in defi is that dforce's $25 million digital assets have been stolen from the lending market. However, the funds were withdrawn because the attacker's IP address was found and shared with the Singapore police
the Xueshuo innovation blockchain Technology Workstation of Lianqiao ecation online is the only approved "blockchain Technology Specialty" pilot workstation of "smart learning workshop 2020 Xueshuo innovation workstation" launched by the school planning, construction and development center of the Ministry of ecation of China. Based on providing diversified growth paths for students, the professional station promotes the reform of the training mode of the combination of professional degree research, proction, learning and research, and constructs the applied and compound talent training system
6. It is impossible
the total amount of Boca issued after the split is 1 billion. If Boca rises to 10000 yuan, its market value will reach 10 trillion yuan, and the total market value of global gold is about 8 trillion US dollars. Boca can't replace gold, so Boca can't rise to 10000 Yuan
Polkadot is a blockchain agreement, It aims to support multiple chains within a blockchain network. It aims to overcome a problem in the current blockchain environment: hundreds of blockchains exist in isolation and have little communication ability
History of Polkadot
Polkadot was developed by parity technologies and led by Gavin wood and Jutta Steiner, two former Ethereum executives. The project is also supported by the Web3 foundation, a closely related organization that provides funding, advocacy, research and cooperation for the project
parity was established in 2015. Initially, it began to develop node software only for Ethereum, known as the parity Ethereum client. The company has phased out its support for the project, allowing it to focus on Polkadot and its related project, substance
development started in November 2017, when developers released the first piece of code on GitHub
the company launched two proof of concept in mid-2018 and deployed Polkadot's first parallel chain in July 2018. Polkadot will be launched as "initial" in May 2020, and token transfer will be launched in August 2020
as of September 2020, Polkadot's relay chain has not been activated, and the on chain auction has not been launched
the total amount of Boca issued after the split is 1 billion. If Boca rises to 10000 yuan, its market value will reach 10 trillion yuan, and the total market value of global gold is about 8 trillion US dollars. Boca can't replace gold, so Boca can't rise to 10000 Yuan
Polkadot is a blockchain agreement, It aims to support multiple chains within a blockchain network. It aims to overcome a problem in the current blockchain environment: hundreds of blockchains exist in isolation and have little communication ability
History of Polkadot
Polkadot was developed by parity technologies and led by Gavin wood and Jutta Steiner, two former Ethereum executives. The project is also supported by the Web3 foundation, a closely related organization that provides funding, advocacy, research and cooperation for the project
parity was established in 2015. Initially, it began to develop node software only for Ethereum, known as the parity Ethereum client. The company has phased out its support for the project, allowing it to focus on Polkadot and its related project, substance
development started in November 2017, when developers released the first piece of code on GitHub
the company launched two proof of concept in mid-2018 and deployed Polkadot's first parallel chain in July 2018. Polkadot will be launched as "initial" in May 2020, and token transfer will be launched in August 2020
as of September 2020, Polkadot's relay chain has not been activated, and the on chain auction has not been launched
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