Al force algorithm
computing power is a measure of bitcoin network processing power. That is, the speed at which the computer calculates the output of the hash function. Bitcoin networks must perform intensive mathematical and encryption related operations for security purposes. For example, when the network reaches a hash rate of 10th / s, it can perform 10 trillion calculations per second
in the process of getting bitcoin through "mining", we need to find its corresponding solution M. for any 64 bit hash value, there is no fixed algorithm to find its solution M. we can only rely on computer random hash collisions. How many hash collisions can a mining machine do per second is the representative of its "computing power", and the unit is written as hash / s, This is called workload proof mechanism pow
computing power provides a solid foundation for the development of big data, and the explosive growth of big data poses a huge challenge to the existing computing power. With the rapid accumulation of big data in the Internet era and the geometric growth of global data, the existing computing power can no longer meet the demand. According to IDC, 90% of the global information data is generated in recent years. And by 2020, about 40% of the information will be stored by cloud computing service providers, of which 1 / 3 of the data has value
therefore, the development of computing power is imminent, otherwise it will greatly restrict the development and application of artificial intelligence. There is a big gap between China and the advanced level of the world in terms of computing power and algorithm. The core of computing power is the chip. Therefore, it is necessary to increase R & D investment in the field of computing power to narrow or even catch up with the gap with the developed countries in the world
unit of force
1 KH / S = 1000 hashes per second
1 MH / S = 1000000 hashes per second
1 GH / S = 1000000000 hashes per second
1 th / S = 100000000000 hashes per second
1 pH / S = 100000000000 hashes per second
1 eh / S = 100000000000 hashes per second
recently, bitcoin's network computing power has entered the era of P computing power (1P = 1024t, 1t = 1024g, 1g = 1024m, 1m = 1024k). In the soaring computing power environment, the arrival of P era means that bitcoin has entered a new stage of arms race. This is the meaning of computing power. I would like to know more about it Please accept)
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What does 1p mean
first of all, 1p computing power is equivalent to about 1.05 million g, which means that if you have 1g computing power of the whole network, you can get almost 1.05 million of bitcoin output of the whole network. According to the output of 3800 bitcoins per day, we can see that the daily income of 1g of computing power has dropped to 0.0036 bitcoins, which is about 2.7 yuan according to the current market price. If the electricity cost and mining machinery hardware cost are included, the profit is almost gone
secondly, 1p's whole network computing power seems amazing, but in fact, in a year's time, you will think it's just a pediatrics, because cointera will launch 2p miner in December, and bitmine will launch 4P miner in March next year. If these companies are not put in biochemical weapons by Syria, it should be expected that bitcoin's whole network computing power will reach more than 10p in a year's time, By then, 1g of computing power will only be able to dig 0.00036 bitcoins a day.
computing power refers to computing power, refers to that in the process of getting bitcoin through "mining", we need to find its corresponding solution M. for any 64 bit hash value, there is no fixed algorithm to find its solution M. we can only rely on computer random hash collisions. How many hash collisions can a mining machine do per second, is the representative of its "computing power". The unit is written as hash / s, which is the so-called proof of work mechanism (POW)
in the process of getting bitcoin through "mining", we need to find its corresponding solution M. for any 64 bit hash value, there is no fixed algorithm to find its solution M. we can only rely on the computer's random hash collisions. How many hash collisions can a mining machine do per second is the representative of its "computing power", and the unit is written as hash / s, This is the so-called proof of work mechanism (POW)
recently, bitcoin's network computing power has entered the era of P computing power (1P = 1024t, 1t = 1024g, 1g = 1024m, 1m = 1024k). In the ever-increasing computing power environment, the arrival of P era means that bitcoin has entered a new stage of arms race
computing power is a measure of the total computing power of the unit that generates new blocks under certain network consumption. The single blockchain of each coin varies with the time required to generate a new transaction block.
New York Central Park is a paradise for joggers. You can bring the latest Bluetooth headset device, and a real-time fitness coach will accompany you. It will not only give you suggestions according to your real-time running speed, but also play your favorite music for you, and even make you laugh
every day at the airport, the sweet looking airline ground crew kindly solves all kinds of problems for you. No matter how tricky the customers are, they can always smile and even provide practical travel suggestions to the passengers when solving the problems. Yes, the difference from the past is that the ground crew may be just a high-precision guidance robot
in every corner of the earth, the revolution of AI is unfolding. The butterfly effect, even a small change, will form a huge storm around us. Everyone knows that this is a technological innovation about the future of mankind, and with the development of 5g, AI will also be earth shaking<
artificial intelligence, like the Internet, has been everywhere
twenty years ago, we just got rid of analog signals, digital communication wave is sweeping, the Internet is just a strange synonym in textbooks, it is difficult for ordinary people to realize that the Internet will redefine the world. Nowadays, the world built by high-speed network lock has become more and more close. Search engines such as Google and the Internet have become our access to information, and social applications such as Facebook have become necessities of life. The e-commerce platform led by Alibaba not only has a serious impact on offline channels, but its size is even large enough to challenge the world's fifth largest economy
from basic necessities of life to cutting-edge science, the Internet has become the world's dominant, and artificial intelligence will undoubtedly become the next "hot spot" in the world
2017 is also a crucial year for 5g development. In this year, 3GPP officially entered the stage of 5g standardization research. Since the MWC in Barcelona in February, 5g has been an absolute hot topic in almost any science and technology exhibition
in fact, experiments on 5g network in China have been launched, and Qualcomm, together with ZTE and China Mobile, has completed the interoperability test of the world's first 5g new air port specification. The new technology achieves the transmission rate of several thousand megabits per second and lower delay in the experiment. Imt2020 (5g) propulsion group has officially released the first batch of specifications for the third phase of 5g technology R & D test, and a number of companies, including Qualcomm, have also contributed to the deployment of new air ports based on R15 specification. Among them, Qualcomm's millimeter wave technology and snapdragon x505g modem series procts are also important technology promoters.
original title: 2019 Chinese artificial intelligence instry market analysis: development bubble graally disappeared, talent development is the key
2019 global development of artificial intelligence instry analysis
from the Japanese classic animation "shell attack mobile team" artificial intelligence (AI) technology application, to the recent Hollywood film "Aleta: Angel of war" robot, in science fiction movies, AI has become one of the most common topics
and the real world outside the screen, whether it is a security camera with iris recognition, or an autopilot equipped with Autopilot (automatic assisted driving), the use of AI technology, like water and electricity, has begun to permeate every aspect of economic and social development. p> The investment of capital accelerates the development of AI. Mmcventures, a British venture capital fund that focuses on start-up investment, recently released a research report on AI (hereinafter referred to as "the report"), which shows that the investment capital of early-stage AI companies in the world has increased 15 times in five years, and is estimated to reach 15 billion US dollars (about 100.8 billion yuan) in 2018
the United States, the largest country of artificial intelligence technology, continues to lead with all its strength. A few days ago, the White House launched a new official website "AI. Gov" to publish the specific measures taken by various federal agencies in the United States to implement the "all government" strategy of artificial intelligence. The website shows that the Special Committee on artificial intelligence under the US National Science and Technology Council will be responsible for coordinating 15 federal agencies to promote the research and development of artificial intelligence technology
and it's not just the technology and enterprises that have multiplied under the popularity
the above report points out that among the 2830 companies in Europe that are labeled as artificial intelligence, 1580 meet the definition of artificial intelligence companies, that is to say, 40% of the companies have nothing to do with artificial intelligence. The research team also found that "if a company is labeled as AI, it can get 15% - 50% more financing."
Wang Yanfeng, vice president of the school of electronic information and electrical engineering of Shanghai Jiaotong University, told first finance that this phenomenon not only occurs in Europe, but also exists in the world. Any revolutionary thing will be accompanied by the emergence of bubbles, which is also an inevitable rule of instrial development. However, with the continuous integration of artificial intelligence and traditional instries, under the constant shock and elimination, the "real gold" companies that can stand the fire are still left
the scale of China's AI market will reach 28 billion in 2019
the scale of China's AI market is growing continuously. According to the analysis report on market outlook and investment strategic planning of China's artificial intelligence instry published by foresight Instry Research Institute, the scale of China's artificial intelligence market will reach 15.21 billion yuan in 2017, with a growth rate of 51.2%. With the graal maturity of artificial intelligence technology, the in-depth layout of technology, manufacturing and other instry giants, and the continuous expansion of application scenarios, it is preliminarily estimated that the scale of China's artificial intelligence market will exceed 20 billion yuan in 2018, reaching about 23.82 billion yuan, with a growth rate of 56.6%. It is predicted that the scale of China's AI market will reach about 28 billion yuan in 2019 2014-2019 China's artificial intelligence market size and growth forecast data source: the prospect Instry Research Institute collate Chinese artificial intelligence foam is graally disappearing "initially (2012) did AI did not meet several AI technology companies." Speaking of the scene when I started my business, co-founder of video + + polar chain technology group & amp; Coo Dong Hui told China first finance and economics according to his recollection, since 2016, there have been more and more AI companies in China, among which there are some real AI companies, but there are also some Internet companies and even traditional advertising companies at present, artificial intelligence technology is in the third climax of development, with machine learning, especially deep learning as the core, developing rapidly in vision, voice, natural language and other application fields. Even with the strong support of capital and policy, there are still many uncertainties in the transformation of practical application scenarios
"in 2015, we opened up the AI algorithm, but found that the algorithm could not be applied, so we increased the investment, and it took more than two years to achieve the real application. Now many entrepreneurs are actually releasing demo (an unformed beta algorithm). Whether it can be implemented is another matter. " He pointed out
in addition, e to the high technical threshold of AI companies, in the process of development, not only those companies with gimmicks will show their feet, but also real AI companies may close down e to the lack of data and technology
"there are two big problems for small start-up AI Enterprises: limited data sets, and no killer applications in business, so they are likely to be unable to support them." Wu Pengyang, deputy director of the instrial research center of Tencent Research Institute, told China first finance and economics
However, with the transformation of traditional instries, the trend of AI convergence in various vertical instries is becoming more and more obvious. According to the report, more than a third of enterprises are expected to deploy AI by the end of 2019. At the same time, there are some new changes in the instry and capitalWu Pengyang said that since 2017, global investment in artificial intelligence has become cautious. At present, the instry has begun to move from online to offline, and manufacturing instry is a typical example
"AI can play a good role in the situation of rising labor costs and low proction efficiency. The manufacturing instry is relatively complex, so this is a single point breakthrough process. The typical application is image recognition. For example, the accuracy of quality inspection can even exceed people's processing level. " Wu Pengyang said. At the same time, he believes that future breakthroughs in the field of public services such as health care and ecation have more potential, because AI can solve the problem of uneven distribution of high-quality resources and stimulate the data potential of such public services
China is dominant in the application layer
from the level, AI mainly has three layers: basic layer, technology layer and application layer. European and American countries started early and invested heavily in the basic layer, while many companies emerged in the application layer and technology layer in China
the above report shows that the number of AI technology companies in the Asia Pacific region is twice that in North America. Among them, Chinese companies lead the Asia Pacific AI, and Beijing, Shanghai, Guangdong, Zhejiang and Jiangsu are the main gathering places
compared with Europe and the United States, the similarities and differences of AI instry development in China are also very clear
Shang Hailong, general manager of Shangtang Technology Hong Kong Co., Ltd., told China first finance and economics that the development of China's AI instry pays more attention to landing applications, and at the same time, it is constantly improving the strengthening of basic research and the construction of original infrastructureand the implementation of application scenarios can not be underestimated for the traction of original basic research and platform construction. The huge market application stimulates and reverses the basic layer, which is the biggest characteristic and advantage of China's AI instry different from that of Europe and the United States
according to the white paper on the development of artificial intelligence instrial application issued by the China Academy of information and communication at the end of last year, in terms of instrial scale, the domestic artificial intelligence market scale reached 23.74 billion yuan in 2017, an increase of 67% compared with 2016. Among them, computer vision market with biometrics, image recognition, video recognition and other technologies as the core has the largest scale, accounting for 34.9%, reaching 8.28 billion yuan
whether it is the "intelligence +" mentioned for the first time in this year's government work report, the "guidance on promoting the deep integration of artificial intelligence and real economy" deliberated and adopted by the central Deep Reform Commission on the 19th, and the "three year action plan for promoting the development of a new generation of artificial intelligence instry (2018-2020)" issued by the Ministry of instry and information technology at the end of 2017, all give AI + traditional instries more possibilities
Wang Yanfeng said that China's "Internet plus" has been put forward for 4 years, and the new round of "intelligence +" is the natural progression and upgrading of the instry. The Internet plus solves data, and the core of AI is data algorithm. Data development is not enough to be intelligent. Now, after several years of development, the digital process has been further improved, so it can be combined with artificial intelligence to proce new formats. " He predicted that in the next three to five years, "intelligent +" traditional instries will have obvious deep integration
According to the latest data, Yu Dian, researcher of Tencent Research Institute, who has been tracking the AI instry for a long time, told reporters that in the world, there are 20 universities in the UK, 168 in the United States, 20 in China in 2017, and more than 30 universities in 2018. That is to say, there are nearly 400 universities with AI direction in the world, To meet the world's millions of needsthe shortage of AI talents in China is at least more than 1 million. Moreover, because the training time of qualified AI talents is much longer than that of general IT talents, it is difficult to effectively fill the talent gap in the short term. " Yu Dian said that AI has very high technical requirements. Although non major students can learn relevant AI knowledge, such as computer major, they can do relatively elementary AI development after one year of learning neural network, but deep basic development still needs highly skilled AI talents
According to Yu Dian, the basic development talents are also the most scarce in China's AI market. Wang Yanfeng said that the advantage of China's AI field lies in the rich talents at the application end. "The scene is rich, and the discipline catalog of the Ministry of ecation is also following up, so there are more talents at the application level." But after all, it started late, and there is still a big gap between high-end and cutting-edge talents and foreign countries However, Dong Hui believes that the salary of AI talents should be combined with the specific situation of the company. For example, the vertical application-oriented AI company does not need to reserve a large number of high-end AI talents. Although there are dozens of doctors in the company, most of them are masters“ A lot of business processes don't need a doctor, and master's students can completely grasp it. " He said that in the company AI, the income gap between different levels of talents is also large, and there is even no upper limit for top-level talents1. Computer vision technology uses the sequence composed of image processing operation and machine learning technology to decompose image analysis tasks into small tasks that are easy to manage
2. Machine learning: machine learning is to automatically discover patterns from data. Once patterns are found, they can be predicted. The more data they process, the more accurate the prediction will be
3. Natural language processing: the processing of natural language text refers to the ability of computer to process text similar to that of human beings. For example, automatically identify the person and place mentioned in the document, or extract the terms in the contract to make a table
4. Robotics: in recent years, with the improvement of algorithms and other core technologies, robots have made important breakthroughs. For example, UAV, domestic robot, medical robot, etc
5. Biometrics technology: biometrics can integrate computer, optics, acoustics, biosensors and biostatistics, and use the inherent biological characteristics of human body, such as fingerprint, face, iris, vein, voice and gait, to conct personal identification, which was initially used in judicial identification.