How does artificial intelligence combine with large data?

Source: Internet
Author: User
Keywords Artificial intelligence large data
Tags analysis analysis methods apple based big data computer data driving

AI needs large data support

Artificial intelligence has three main branches:

1. rule-based Artificial Intelligence;

2. No rules, the computer reads a large amount of data, according to data statistics, probabilistic analysis methods, intelligent processing of artificial intelligence;

3. A deep learning based on neural networks.

Based on the rules of artificial intelligence, in the computer according to the prescribed grammatical structure input rules, using these rules for intelligent processing, lack of flexibility, not suitable for practical. Therefore, the actual mainstream of artificial intelligence is the latter two.

Then both are through "the computer reads the massive data, promotes the artificial intelligence itself the ability/the accuracy". Today, after a lot of data generation, there are low-cost storage to store it, with high-speed CPU to deal with it, so the artificial intelligence after two branches of the theory to practice. Thus, artificial intelligence can make close to human processing or judgment, improve accuracy. At the same time, the use of artificial intelligence services as high value-added services, become the main factor to obtain more users, and the increasing number of users, resulting in more data, so that artificial intelligence further optimization.

Large data mining without artificial intelligence technology

Large data is divided into "structured data" and "unstructured data".

"Structured data" refers to the enterprise's customer information, business data, sales data, inventory data, etc., stored in the ordinary database, specifically refers to the database can be managed as a data. In contrast, "unstructured data" refers to data that is not stored in a database, including e-mail, text files, images, videos, and so on.

Currently, unstructured data is proliferating, and about 80% of enterprise data is unstructured. With the advent of social media, unstructured data has been greeted with a burst of growth. Complex, massive amounts of data are often referred to as large data.

However, the analysis of these large data is not simple. Text mining needs "natural language processing" technology, image and video parsing needs "image parsing technology". Today, speech recognition technology is also indispensable. These are the techniques studied in the field of artificial intelligence in the traditional sense.

Large data and artificial intelligence in search engines

The best combination of big data and artificial intelligence is Google and Apple.

Google to provide optimized search engine services, the background of artificial intelligence with the use of users and constantly evolve, the use of more users, search engines will be more optimized, optimized, users naturally more. In addition to search engines, Google also through Gmail, Google Docs, etc. to obtain a large number of "unstructured data." As a result, Google's brain becomes smarter.

In addition, Google has developed a "semantic search" of the evolutionary system, Apple's speech recognition technology Siri is based on the latest artificial intelligence theory (depth learning) built.

In turn, the evolution of modern artificial intelligence requires not only theoretical research but also a large amount of data as raw material.

Large data and artificial intelligence in automobiles

At the beginning of 2014, Google joined Audi, GM, Honda, Hyundai and Nvidia to set up a new consortium: The Open Automotive Alliance, and Apple, which dabbled in the auto industry last June, unveiled the "IOS in the" Car "(through the Siri voice operation can achieve navigation, call, music playback and other services).

Recently, Google announced that it will be in 2017 to the market to invest in self-driving cars, August 2013 has completed a 480,000-kilometer test drive. The large data of the 480,000 km test drive has become the driving experience data, which provides the decision analysis basis for the automatic driving of artificial intelligence.

Subversive innovation comes from big Data + artificial Intelligence

Google and Apple have brought a deep sense of crisis to traditional industries such as automobiles. And their subversive innovation, in fact, from the combination of large data and artificial intelligence. Perhaps this is well worth our thinking. Will the same phenomenon, the same subversion, take place in more, or even all, other traditional industries?

The Center for International Economic and Technical cooperation, Ministry of Industry and Information technology Wang Xiwen

(Responsible editor: Mengyishan)

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