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Polkadot blockchain browser
Publish: 2021-05-08 04:10:34
1.
POW: full name of proof of work
pos: proof of stake
both of them are the consensus mechanism of blockchain and the bookkeeping method of digital currency
the difference is:
1. POW mechanism: workload proof mechanism, that is, the proof of workload, is the requirement that must be met when generating a new transaction information (that is, a new block) to be added to the blockchain. In the blockchain network based on workload proof mechanism, the ability of nodes to obtain the correct numerical solution to generate blocks by calculating the numerical solution of random hash hash is the specific performance of node computing power
POS mechanism: the proof of rights and interests requires the certifier to provide a certain amount of ownership of cryptocurrency. The operation mode of the proof of rights and interests mechanism is that when creating a new block, the miners need to create a "currency right" transaction, and the transaction will send some coins to the miners themselves according to the preset proportion. According to the proportion and time of token owned by each node, the equity proof mechanism reces the mining difficulty of nodes proportionally according to the algorithm, so as to speed up the speed of searching for random numbersextended materials:
the concept of bitcoin was first proposed by Nakamoto in 2009. According to Nakamoto's ideas, the open source software and the P2P network on it were designed and released. Bitcoin is a kind of P2P digital currency. Point to point transmission means a decentralized payment system
unlike most currencies, bitcoin does not rely on specific currency institutions. It is generated by a large number of calculations based on specific algorithms. Bitcoin economy uses the distributed database composed of many nodes in the whole P2P network to confirm and record all transactions, and uses the design of cryptography to ensure the security of all aspects of currency circulation. The decentralized nature and algorithm of P2P can ensure that it is impossible to artificially manipulate the value of bitcoin through mass proction
2. [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"
3. 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
4.
Dot is not a coin“ "Dot" means that the tire meets the safety standards specified by the U.S. Department of transportation (DOT)“ The 11 digits and letters immediately after "dot" indicate the identification number or serial number of the tire. Dot is divided into three levels: A, B and C, of which the C level is the lowest, only reaching the minimum performance conditions specified by the U.S. Department of transportation (DOT). The other two levels are higher than the standard required by dot
extended data:
the application research of dot mainly focuses on the following aspects:
1. Optical breast imaging technology early diagnosis of breast tumor
2. Observation of oxygen supply and blood oxygen dynamics ring neonatal brain development
Brain functional imaging4
5. Unknown_Error
6. Step 1: buy an English Chinese Dictionary
Step 2: open the dictionary and find the words
Step 3: follow the phonetic alphabet
Step 4: recite it and check it with the teacher tomorrow morning
Step 2: open the dictionary and find the words
Step 3: follow the phonetic alphabet
Step 4: recite it and check it with the teacher tomorrow morning
7. Ichinaiji (the main theme) - Polka Dot stingray ō Sha Shinaide
Watakushi Da TTE Fu Keiki ō
< > > ō GA Hosh ī< Yosoiki Ni Mainichi
mamirete Fuan Desh ō<
< ī Endo no sh ō I want to have a favorite answer ō GA Hosh ī< Yosoiki Ni Mainichi
mamirete Fuan Desh ō< Suki Na UTA Nara utaitai
Hosh ī Monnara
zenbu motteru to
omote ITA KEDO, tarinai
Watakushi no S ō Z ō
< >
I guess you & 39;
ā< Sakebu I need you
ō Ni kisoisaite Mo
free! Nante ittatte fur ī K ī< I guess you re right darling
Sonna N J ā< Watakushi Ni wa wakaranai
ō<
< tt / > < tt / > < tt / > < EM / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < ō Jo de Itai
Urahara Ni jibun o
JAMA shite grandai ū To hanpa de irarenai
Itai Koto Nara Itsu Mo matteru to
wakatte IRU Kara, matanai
kakatte Koi yobab
ā Ideyofire
k ū Zen zetsugo nomotion ī Wake wa Shinaide ō Na Watakushi o mite yo
screaming
Hont ō I don't like it, but I don't like it
ā< Sakebu I need you
ō Ni kisoisaite Mo
free! Nante ittatte fur ī K ī<
Ni hairanai wa
Moeru y ō Na Hitomi o shite IRU
deadline Zettai REI do nopassion
konna Ichi Daji
yosoki wa sutete
mukae Ni kite
Watakushi Da TTE Fu Keiki ō
< > > ō GA Hosh ī< Yosoiki Ni Mainichi
mamirete Fuan Desh ō<
< ī Endo no sh ō I want to have a favorite answer ō GA Hosh ī< Yosoiki Ni Mainichi
mamirete Fuan Desh ō< Suki Na UTA Nara utaitai
Hosh ī Monnara
zenbu motteru to
omote ITA KEDO, tarinai
Watakushi no S ō Z ō
< >
I guess you & 39;
ā< Sakebu I need you
ō Ni kisoisaite Mo
free! Nante ittatte fur ī K ī< I guess you re right darling
Sonna N J ā< Watakushi Ni wa wakaranai
ō<
< tt / > < tt / > < tt / > < EM / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < tt / > < ō Jo de Itai
Urahara Ni jibun o
JAMA shite grandai ū To hanpa de irarenai
Itai Koto Nara Itsu Mo matteru to
wakatte IRU Kara, matanai
kakatte Koi yobab
ā Ideyofire
k ū Zen zetsugo nomotion ī Wake wa Shinaide ō Na Watakushi o mite yo
screaming
Hont ō I don't like it, but I don't like it
ā< Sakebu I need you
ō Ni kisoisaite Mo
free! Nante ittatte fur ī K ī<
Ni hairanai wa
Moeru y ō Na Hitomi o shite IRU
deadline Zettai REI do nopassion
konna Ichi Daji
yosoki wa sutete
mukae Ni kite
8. Itsy Bitsy Teeny weenie yellow Polkadot bikini should be an American song
9.
Yes
LUO Tianyi, the world's first Chinese v virtual singer, officially appeared on July 12, 2012. In 2015, Shanghai Tianya heinian company integrated its virtual singers and creatively launched the virtual singer brand vsinger
so far, Luo Tianyi's original songs have reached more than 7000, and are still increasing at the rate of nearly 100 songs per month. One of Luo Tianyi's famous works, Quan Yu Tian Xia, has played 5 million MVs on station B with more than 1000 related second creation videos
performance record
1, seeu holographic concert
on January 19, 2013, in the concert of seeu, the virtual image of VOCALOID in South Korea, Luo Tianyi guest starred and sang "66ccff" composed by Sugita Lang
2. Shanghai holographic show
LUO Tianyi held the holographic show in Shanghai from December 5 to 8, 2014. The songs include "Star", "be my boy", "feel your dream" and so on
From September 19 to 21, 2015, Luo Tianyi, Le Zhengling and Yanhe held three holographic shows together. The songs include scarlet drop, ordinary disco, feel your dream, half and half, etc4. On the evening of February 2, 2016, Luo Tianyi boarded the 2016 Hunan Satellite TV Spring Festival Gala, and sang "Hua Er Na Ji" with her partner Yang Yuying
On July 23, 2016, luotianyi's new image of vocaloid4 appeared in bilibilibili macro link in the form of holography, singing "66ccff", "night dance" and "connect the heart"10. There are a lot of materials to supply or annihilate gante, boss blood card
if you annihilate boss 30, some materials
in addition, annihilation can brush electric saw, but annihilation is more difficult.
it is suggested to supply king, annihilate warrior
PS: boss powder has nothing to do with map difficulty
if you annihilate boss 30, some materials
in addition, annihilation can brush electric saw, but annihilation is more difficult.
it is suggested to supply king, annihilate warrior
PS: boss powder has nothing to do with map difficulty
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