Artificial intelligence computing power
According to reports, the 2017 Intel China instry summit was held in Suzhou yesterday. At the meeting, Dr. Jerry Kaplan, an internationally renowned AI expert and technological innovation entrepreneur, delivered a speech, explaining the development of artificial intelligence and how it can lead instrial change
The rise of 
machine learning is inseparable from the rapid growth of computer computing power. In the past 30 years, the speed of computer has increased by 1 million times. If we compare the speed of computers 30 years ago to that of snails, now it's like the speed of rockets
when the speed of the computer is faster and faster and the amount of data is large, machine learning becomes a better match, especially when we are about to enter the 5g era, which further promotes the interaction between dection and reasoning, perception and the real world. In the future, we can build a new flexible robot with strong perception ability
I hope artificial intelligence technology can achieve greater development
nowadays, China's artificial intelligence is not short of data, and its computing power is also constantly improving. However, because the algorithm is not mature enough and there is no original algorithm of its own, many false artificial intelligence appear. To put it mildly, it can be called weak artificial intelligence and weak AI.
The principle of artificial intelligence can be simply described as:
Artificial Intelligence = mathematical calculation
the intelligence of the machine depends on the "algorithm". At first, it was found that 1 and 0 could be represented by the on and off of the circuit. If many circuits are organized together and arranged differently, they can express many things, such as color, shape and letters. In addition, the logic element (triode) forms the "input (press the switch button) - Calculation (current through the line) - output (light on)"
but in go, there is no way to exhaust it like this. No matter how powerful, there are limits. The possibility of go is far beyond the sum of all atoms in the universe (known). Even if we use the most powerful supercomputing at present, it will take tens of thousands of years. Until quantum computers were mature, electronic computers were almost impossible< Therefore, the programmer adds an extra layer of algorithm to the alpha dog:
A. calculate first: where you need to calculate, where you need to ignore
B. then, the calculation is targeted
-- in essence, it's computation. There is no "perception"
in step a, how can it judge "where to calculate"
this is the core problem of "artificial intelligence": the process of "learning"
think about it carefully. How do humans learn
all human cognition comes from summing up the observed phenomena and predicting the future according to the law of summing up
when you see a four legged, short haired, medium-sized, long mouthed, barking animal named dog, you will classify all similar objects you will see in the future as dogs< However, the way of machine learning is qualitatively different from that of human beings:
by observing a few features, human beings can infer most of the unknowns. Take one corner and turn three
the machine must observe many dogs to know whether the running dog is a dog
can such a stupid machine be expected to rule mankind
it's just relying on computing power! Strength is the key to success
specifically, its "learning" algorithm is called "neural network" (more bluffing)< It needs two preconditions:
1. Eat a lot of data to try and error, and graally adjust its accuracy; 2
2. The more layers of neural network, the more accurate the calculation (with limit), and the greater the calculation force
therefore, neural network has been used for many years (it was also called "perceptron" at that time). However, limited by the amount of data and computing power, it has not developed
it sounds like neural networks don't know where the high end is! This once again tells us how important it is for us to have a nice name
now, these two conditions have been met big data and cloud computing. Who has data, who can do AI< At present, the common application fields of AI are as follows:
Image Recognition (security recognition, fingerprint, beauty, image search, medical image diagnosis) uses "convolutional neural network (CNN)", which mainly extracts features of spatial dimension to identify images
natural language processing (human-computer conversation, translation) uses "recurrent neural network (RNN)", which mainly extracts the features of time dimension. Because there is a sequence of words, the time when words appear determines the meaning
the design level of neural network algorithm determines its ability to depict reality. Wu Enda, the top Daniel, once designed convolution layers up to 100 layers (too many layers are prone to over fitting problems)
when we deeply understand the meaning of calculation: there are clear mathematical laws. Then,
the world has quantum (random) characteristics, which determines the theoretical limitations of computer—— In fact, computers can't even generate real random numbers
-- machines are still clumsy
for more in-depth AI knowledge, you can ask in private letters
as human beings, when they encounter something in a certain scene, they complete an intelligent process from perception (data collection) to cognition (law discovery) and then to decision-making. For a matter, the degree of satisfaction of each person's way of dealing with it is different. Taken together, it is effectiveness, which can be quantified. Similarly, machines imitate human intelligence, and the way they deal with things is also effective, which can be called artificial intelligence efficiency, and can also be quantified
with the development of computer, the computing power of computer far exceeds that of human beings, so the contribution of computing power in artificial intelligence is huge and the most deterministic factor. With the development of artificial intelligence chip, the development of algorithm is faster and faster. In the foreseeable future, with the emergence of quantum computer, The contribution of computing power in artificial intelligence may surpass data and become a decisive factor. Even if there is no breakthrough in the algorithm, the efficiency of artificial intelligence will be improved
with the deepening of information application, information systems can perceive the world like people, and huge amounts of data are generated in various scenarios every moment to enter the information system, which is big data. Compared with the ancients, the modern society proces more data that can be used by the information system in one day than the ancient society in a few years. Therefore, with the deepening of the application of information technology, artificial intelligence has made a breakthrough, which can be said to be the credit of big data
there is no big difference between the ancient and modern people's computing power, but the ancient people relied on their own computing power to accurately create astronomical calendar and other achievements with limited data. The ancients used the advanced algorithm of the book of changes to predict many phenomena. It can be seen that the multiplication effect of the algorithm makes the human intelligence efficiency increase geometrically
artificial intelligence has surpassed human beings in some fields, and its efficiency has surpassed human beings by several orders of magnitude. It can be said that it is the result of the comprehensive effect of computing power, algorithm and big data, and the contribution of computing power and data is especially great
hope to help you!!
artificial intelligence, abbreviated as AI. It is a new technical science to research and develop the theory, method, technology and application system for simulating, extending and expanding human intelligence. Artificial intelligence is a branch of computer science. It attempts to understand the essence of intelligence and proce a new intelligent machine that can respond in a way similar to human intelligence. The research in this field includes robot, language recognition, image recognition, natural language processing and expert system. Artificial intelligence is a new technology science which researches and develops the theory, method, technology and application system for simulating, extending and expanding human intelligence. Since the birth of artificial intelligence, the theory and technology have become more and more mature, and the application field has been expanding, but there is no unified definition
artificial intelligence is the simulation of the information process of human consciousness and thinking. Artificial intelligence is not human intelligence, but it can think like human and may surpass human intelligence. But this kind of advanced AI that can think for itself still needs a breakthrough in scientific theory and engineering
artificial intelligence is a very challenging science. People engaged in this work must understand computer knowledge, psychology and philosophy. Artificial intelligence is a very wide range of science, it is composed of different fields, such as machine learning, computer vision and so on. Generally speaking, one of the main goals of artificial intelligence research is to enable machines to be competent for some complex tasks that usually need human intelligence to complete. But different times and different people have different understanding of this kind of "complex work"
the definition of artificial intelligence can be divided into two parts, namely "artificial" and "intelligence"“ "Artificial" is easy to understand and not controversial. Sometimes we have to consider what human beings can proce, or whether the level of human intelligence is high enough to create artificial intelligence, and so on. But generally speaking, "artificial system" is the artificial system in the general sense
there are many questions about "intelligence". This involves others such as consciousness, self and mind (including unconsciousness)_ Mind) and so on. It is generally accepted that the only intelligence people understand is their own intelligence. However, our understanding of our own intelligence is very limited, and our understanding of the necessary elements of human intelligence is also limited, so it is difficult to define what "artificial" manufacturing "intelligence" is. Therefore, the research of artificial intelligence often involves the research of human intelligence itself. Other intelligence about animals or other artificial systems is also generally considered as a research topic related to artificial intelligence
artificial intelligence has been paid more and more attention in the field of computer. It has been applied in robot, economic and political decision-making, control system and simulation system.
in this inevitable conflict, we must solve this problem. To sum up, in this case, today, we need to solve the problem of the appearance of artificial intelligence. Generally speaking, if the appearance of artificial intelligence appears in our life, we have to consider the fact that it appears. Artificial intelligence looks like what will happen if it doesn't happen. I hope that all of you will have a discussion in the spirit of saying everything you know, saying everything you say, saying nothing and hearing enough. To sum up, Ellis inadvertently said that there are dangers on land that the sea does not know. This sentence, like my intimate companion on the journey of life, constantly inspires me to move forward. Now, it is very, very important to solve the problem of what artificial intelligence looks like. Therefore, the proverb summed up their own life experience into such a sentence, people are noble and ambitious, learning is noble and constant. This sentence, like my intimate companion on the journey of life, constantly inspires me to move forward. France once said that if we don't live by the known truth first, we can't seek the truth. This sentence seems simple, but the gloom in it makes people think deeply. I hope that all of you will have a discussion in the spirit of saying everything you know, saying everything you say, saying nothing and hearing enough.
in recent years, artificial intelligence has made everyone feel its very hot and sustainable development. Therefore, we believe that this round of rapid development of artificial intelligence benefits from the rapid development of IT technology over the years, which brings computing power and computing distance to artificial intelligence, so as to provide support for artificial intelligence algorithms
in recent years, the research and development of artificial intelligence technology and various artificial intelligence applications by enterprises have been continuously implemented, which directly promotes the rapid development of the overall artificial intelligence instry. The overall scale of the core instry of artificial intelligence is close to 100 billion yuan, which can be said to be one of the instries with huge scale. Moreover, from the perspective of future development trend, it is estimated that this year, the overall market scale will reach 160 billion yuan, so the growth rate is still very fast
What are the advantages of deep learning
in order to recognize a certain pattern, the usual way is to extract the features of the pattern in a certain way. This feature extraction method is sometimes designed or specified manually, and sometimes summed up by the computer itself under the premise of relatively more data. Deep learning puts forward a method to let the computer automatically learn the pattern features, and integrates the feature learning into the process of modeling, so as to rece the incompleteness caused by artificial design features. At present, some machine learning applications with deep learning as the core have achieved the recognition or classification performance beyond the existing algorithms in the application scenarios that meet specific conditions
if you are interested in artificial intelligence and deep learning, you can take a look at the AI deep learning courses jointly organized by China public ecation and Chinese Academy of Sciences, both of which are taught by experts of Chinese Academy of Sciences in person