Artificial intelligence refers to the ability of a computer system to perform complex tasks that were originally only possible with human intelligence. The lack of hardware system capabilities and the deviations in the development path, as well as the flaws of the algorithm, made the development of artificial intelligence technology in the 1980s and 1990s. In recent years, the low-cost large-scale parallel computing, big data, deep learning algorithms, and the four catalysts of human brain chips have led to an upward turning point in the development of artificial intelligence.
Big data refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain time frame. It is a massive amount of decision-making, insight, and process optimization capabilities that require new processing models. High growth rates and diverse information assets.
This definition is given to Gartner, the "big data" research organization. “Big Data†is an information asset that requires a new processing model to have greater decision making, insight and process optimization capabilities to accommodate massive, high growth rates and diversification.
Big data is equivalent to the vast amount of human brain's knowledge and memory from primary school to university. This knowledge can only be created by digesting, absorbing, and recreating.
Artificial intelligence makes a metaphor for a person to absorb a large amount of human knowledge, continuous deep learning, evolution into a high person. Artificial intelligence is inseparable from big data, and it is based on cloud computing platform to complete deep learning evolution.
Artificial intelligence is based on the support and collection of big data, and is used to achieve specific performance and calculation methods manually. Big data is the accumulation of data such as continuous collection, precipitation, and classification.
Compared with many previous data analysis techniques, artificial intelligence technology is based on neural networks and develops multi-layer neural networks for deep machine learning. Compared with traditional algorithms, this algorithm has no redundant assumptions (such as linear modeling needs to assume a linear relationship between data), but completely uses the input data to simulate and construct the corresponding model structure. This algorithmic feature determines that it is more flexible and has the ability to self-optimize based on different training data.
But this remarkable advantage brings about a significant increase in the amount of computation. Until the breakthrough in computer computing power, such an algorithm has almost no practical value. About a decade ago, we tried to use a neural network to compute a set of data that was not massive. Waiting for three days would not necessarily result. But today's situation is very different. High-speed parallel computing, massive data, and more optimized algorithms have contributed to the breakthrough in the development of artificial intelligence. This breakthrough, if we look back 30 years later, will be another technology that is not weaker than the Internet has a profound impact on humanity, and the power it releases will once again completely change our lives.
Big data artificial intelligence which is betterArtificial intelligence involves a wide range of fields, applications in industry, aerospace, and commerce, and has penetrated people's lives. Open Cortana or Siri in mobile phones, which is the product of AI. You know, this advanced technology was unrecognized decades ago, and there are very few schools that teach related courses. The reason is mainly the accumulation and application of data. High-capacity storage devices enrich the retention of data volume. As data continues to increase, people begin to discover certain rules in it, triggering the need for analysis.
Analysis makes a lot of data worthwhile, the machine begins to understand what the user wants, can predict the future weather and the score of the game, this combination of artificial intelligence and scene, to achieve is to change lifestyle and liberate productivity. Specifically, many things that only people can do in the past can now be implemented by machines in more cases. Typical examples include voice assistants and driverless cars. More importantly, as hardware performance increases and computing resources become more powerful, the cost is getting lower and lower.
So each has its own good.
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