In a broad sense, the application of artificial intelligence has been very extensive. Major news clients will push relevant news according to your reading interests, major e-commerce platforms will push relevant products according to your purchasing habits, and almost all web pages you browse. The ads presented are all related to your historical searches … these are AI. Moreover, unlike the development of artificial intelligence in the past 60 years, which was mainly concentrated in the laboratory, the new round of artificial intelligence has already exerted its power in many application scenarios. It should be said that the new wave of artificial intelligence has just begun.
From cloud computing to big data, artificial intelligence already has a relatively solid foundation. Among them, big data can be regarded as the means of production on which artificial intelligence depends, while cloud computing is the production tool for the development of artificial intelligence. However, judging from the current development status of artificial intelligence, most artificial intelligence is still in the stage of big data analysis, and there is still a certain distance from true artificial intelligence.
Artificial intelligence is saying goodbye to a new round of concept hype
If the concept of artificial intelligence was proposed 60 years ago, it was somewhat sci-fi, then today the concept of artificial intelligence is hot again but has strong practical significance. Since Google AlphaGo defeated human players in the field of Go, artificial intelligence has started a new round of development boom. Unlike the previous artificial intelligence to defeat humans with powerful algorithms (exhaustive), in the field of Go, artificial intelligence has demonstrated the ability of machine learning.
As a result, 2016 was called the new era of artificial intelligence by the industry. Almost all IT Internet companies, as well as those traditional companies that are still promoting Internet + and digital transformation, also began to seek to use artificial intelligence to achieve their own transformation and upgrading. The new technology represented is becoming the new productivity.
However, in 2016, the focus of enterprises on artificial intelligence remained at the conceptual level, that is to say, enterprises were well aware of the possible opportunities in the field of artificial intelligence and the possible impact of the application of artificial intelligence on traditional industries. However, how to promote the implementation of artificial intelligence and turn these ideas into reality is still a difficult problem.
In this process, enterprises have found that cloud computing and big data are playing an increasingly important role in the development of artificial intelligence. Cloud computing provides computing power and plays the role of production tools ; big data provides data foundation and plays the role of production means.
In terms of the logic of technological development, it is more suitable for artificial intelligence to start from the perspective of cloud computing and big data ; but from the perspective of application, how to realize artificial intelligence through the application of cloud computing and big data still needs a long way to go. to go. It should be said that artificial intelligence is completely consistent with the previous technical concept hype route, and it is also experiencing a transition from excessive deification to landing.
From the perspective of industry applications, those industries that naturally require high computing power and data are opening the door to artificial intelligence applications. As Shen Jin, Qualcomm's global vice president and managing director of venture capital, said, artificial intelligence has entered the second half, and the second half means that its development speed will be much faster than we imagined, and artificial intelligence has been able to rapidly change various industries. This is due to the three driving forces of artificial intelligence: data, network, computing power, each of which is developing at an exponential rate.
And Goldman Sachs chief economist Jan Hatzius also said that in the future, artificial intelligence technology will comprehensively drive the improvement of productivity. Just like the impact of electricity on all walks of life, artificial intelligence will enter many industries such as agriculture, finance, medical care, retail, and energy. , the opportunity is huge.
From big data to machine learning, artificial intelligence is getting better
Although a new era of artificial intelligence has begun, the current development and application of artificial intelligence is still mainly at the level of big data technology: through the analysis of massive data, the corresponding data laws are obtained, thus guiding people to make decisions based on the results of data analysis. optimization to unlock the value of data. As Kai-Fu Lee, CEO of Innovation Works , once said, the first scenario in which artificial intelligence is used is the scenario where big data is well accumulated.
Therefore, many companies engaged in big data analysis have begun to label themselves artificial intelligence. Strictly speaking, doing so is inevitably suspected of being a hot spot, but it is also logical. If the new round of artificial intelligence development is redefined, the in-depth application of big data technology can be regarded as the 1.0 era of artificial intelligence.
Based on data analysis and insight into the secrets of data, the subject here is still people, not machines. However, the emergence of machine learning and deep learning has gradually turned the subject into a machine, and began to reflect the true meaning of artificial intelligence. From human analysis of data to machine learning through data, such a change has far-reaching significance, which can be called the 2.0 era of artificial intelligence.
However, judging from the current development status of artificial intelligence, only a few enterprises can advance to the stage of artificial intelligence 2.0 represented by machine learning . Compared with big data analysis, the emergence of machine learning is the continuous optimization of algorithms based on big data analysis, so that machines can use these algorithms to continuously improve the ability of big data analysis. The algorithm here is like the wisdom and ability that humans endow the machine, from "teaching them to fish" to "teaching them to fish".
From a technical point of view, although the development of artificial intelligence is rapid, from cloud computing, big data to machine learning, it is still in a linear development stage. The real high-level artificial intelligence is that the machine itself has the ability to collect, organize, and analyze data, and can adjust and optimize the algorithm independently, and make independent judgments and decisions. Such artificial intelligence can be called the 3.0 era of artificial intelligence, and it is closer to the ideal artificial intelligence.
From an application perspective, Kai-Fu Lee also gave his own judgment: AI will develop in the following three stages in the next 10 to 15 years: first, AI will occur in industries with a high degree of dataization; second, with perception, With the development of sensors and robots, artificial intelligence will extend to the physical world; eventually artificial intelligence will penetrate into personal scenes.
The next breakthrough point of artificial intelligence: application scenarios
Whether it's chess, Go or Texas Hold'em, whether artificial intelligence can beat humans in such chess and card games has become no suspense. If artificial intelligence can only do so much, the charm of this emerging technology will be greatly reduced.
This is also true. Today, people have become indifferent to this kind of man-machine war, and they have begun to expect this new technology to be applied in almost all work and life scenarios, just like when computers and the Internet first appeared. At that time, the application of computers allowed people to enter a paperless information age, and the application of the Internet allowed people to break the boundaries of information transmission and truly made the world more interconnected.
Judging from the current situation, the revolution brought by artificial intelligence will far exceed that of computers and the Internet, because what it has to do is to replace, or partially replace, human thinking. For example, in the medical industry, a doctor's diagnostic ability largely depends on the doctor's personal medical level and medical experience. Through laboratory data on various indicators of patients, experienced doctors can make more accurate diagnoses, while those of younger doctors are much less accurate. In comparison, artificial intelligence is obviously more advantageous because it can analyze all relevant case data to draw a diagnosis that is closer to the truth.
Healthcare is clearly one of the hot areas where AI can shine. Similar applications of artificial intelligence can also be extended to more scenarios, such as finance, energy, transportation, and even literary and artistic creation and many other industries. What artificial intelligence brings to people is not only to present its laws through data analysis and help people make decisions , but also to avoid human interference from emotions, emotions and other factors, and to help people make more reasonable decisions.
However, compared with the evolution of artificial intelligence technology, the most important task of artificial intelligence at present is how to popularize it in more application scenarios, and really be used by people in these scenarios. Artificial intelligence needs to continuously acquire new data and conduct continuous and in-depth learning. "The more you use it, the better it is" can be said to be the key to the development of artificial intelligence.
From the perspective of current market applications, artificial intelligence is only used in some special fields and special places, and it is far from being popularized, and it is difficult to really play its role. From the laboratory to the popularization, artificial intelligence obviously still has a long way to go.
Therefore, the opportunities for artificial intelligence at this stage are more concentrated in different application scenarios, not just laboratory-level applications.
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