Artificial intelligence and the past and present life of big data

liu, tempo Date: 2021-09-17 09:16:57
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2021 artificial intelligence:Does artificial intelligence come from planned economy? What is the connection between artificial and the past and present life of big data? The important question is whether artificial intelligence comes from planning or from somewhere else? This is the first question. The second question is, where will the development of artificial intelligence take us? Will artificial intelligence bring us to the planned economy? This is the topic I want to discuss today.


Artificial intelligence and the past and present life of big data

In order to discuss this topic, I want to start from the most basic technical level, because I need to understand what artificial intelligence means, what artificial intelligence can and cannot do, and what is the relationship between big data and it. First of all, big data itself is not so important. Its importance lies in that it is the basis of artificial intelligence. Now, the reason why all developed countries in the world pay great attention to the development of artificial intelligence is that this is a rising industrial revolution.


The immediate consequences of this industrial revolution are that a large number of unmanned factories, many unmanned service industries, high efficiency never seen in human history, and a huge number of unemployment.


2021 artificial intelligence


Well, since the technical basis of artificial intelligence is big data, big data has now become a basic resource, just like the raw materials and energy we have experienced in the past in human history. But what is different about this resource is that it does not exist in the world, but we collect it manually.


The following question is, when this production mode basically changes, will this new and comprehensive automation change the system from the basic place? I would like to make a very brief summary. We should learn from the industrial revolution that has taken place in the past. If we do not learn from the past, we will repeat the mistakes.


The reason why the past industrial revolution brought lessons is that when these industrial revolutions came into being, people overestimated where the industrial revolution might go, and when overestimating their own strength, mankind would abuse these emerging science and technology. Let me give two historical examples. The first is the design of such a system as central planning based on state-owned system produced by that technology in that context during the second industrial revolution, which is designed by overestimating people’s planning ability and people’s ruling ability.


Another example is the damage to the environment, such as fossil raw materials. The large-scale use of fossil raw materials came with the first and second industrial revolution, resulting in high global carbon emissions, global warming and a series of pollution. People have realized that it is time to reverse.


These are lessons from the past. Today, when big data and artificial intelligence are combined, we do not know the possible dangers. For example, large companies with monopoly use the data in their hands to try to control society, for large-scale war, for crime, etc.


Let’s take a look at artificial intelligence and big data from the most basic places. Today’s great development of artificial intelligence is actually accumulated from the development of more than half a century in the past.


First of all, the first important part of artificial intelligence is the algorithm, which was explored as early as the 1950s. As for the formulation, algorithms and ideas of artificial intelligence, and even some guiding opinions, few founders determined the name at a meeting in 1956 and discussed the general direction. One of the founders was Professor Simon, the economist, who was the winner of the Nobel Prize in economics, and professor of economics at Carnegie Mellon University The idea of artificial intelligence came from the unification of computer professors and psychology professors.


The best developed algorithm of artificial intelligence is the so-called “neuron model”. The neuron model makes this machine can learn under the guidance of people. The so-called “deep learning” is what people usually mention when talking about artificial intelligence today.


Another commonly used and explorable method of artificial intelligence is “statistical algorithm”, but whether it is artificial training or statistical method, it must have a large amount of data, which is why big data is the foundation.


The second foundation of artificial intelligence is computing power. In the past half century, the computing speed, computing power and storage capacity have basically doubled every two years (Moore’s law). After accumulating for half a century, now the super ability makes the artificial intelligence using any computing method surpass people in some fields, and greatly surpass people, in part because of algorithms, Part of the reason is computing power. Of course, all these are based on big data.


Next, we need to understand the technical basis of big data itself, so that we can understand what artificial intelligence can and cannot do.


First of all, the most basic basis for big data generation is sensors and mobile devices. Sensors and mobile devices first detect some specific data, then transmit them through the Internet and the Internet of things, and then collect them. The core of the so-called big data is to collect, transmit, store and process all the data that these sensors and mobile devices can measure. This is the key. What artificial intelligence can and cannot do is determined by this, that is, whether it can be measured.


Another level of big data is the use of a large number of documents accumulated in history, including documents accumulated by various disciplines. For example, there are text, pictures, music and dance records in the library, which can be converted into big data for machine learning and analysis.


The so-called “deep learning” artificial intelligence (we mostly talk about artificial intelligence today). Its technical basis is to train machines with big data to generate recognition ability, reasoning ability, planning ability, etc. Next we are talking about the algorithm, because the so-called deep learning is actually an algorithm. From the beginning, this thing has been together with the decision-making theory in economics, or in other words, it can be regarded as a part of the decision-making theory.


What is the core of the algorithm? First of all, as a designer of artificial intelligence, you should assign a purpose to your robot, that is, what is the purpose of the machine you built in the world and what is it used for? His purpose is the same as that of our economists – it seeks to maximize its own benefits.


No economist knows what the real purpose of everyone in the world is and what affects you? In the abstract, your purpose is to be happy and happy, but no economics knows what affects your happiness and happiness. That’s why the “market” is important.

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