The difference between artificial intelligence and big data _ which is better for big data artificial intelligence?
What is big data?
Big data refers to a collection of data that cannot be captured, managed and processed by conventional software tools within a certain time range. It is a massive, high-growth and diversified information asset, which needs a new processing mode to have stronger decision-making, insight and discovery, and process optimization ability.
Gartner, a research institute of "big data", gives such a definition. "Big data" is an information asset, which needs a new processing mode to have stronger decision-making, insight and process optimization capabilities to adapt to mass, high growth rate and diversification.
The difference between artificial intelligence and big data _ which is better for big data artificial intelligence?
The difference between artificial intelligence and big data
Big data is equivalent to the vast amount of knowledge that the human brain remembers and stores from primary school to university. Only through digestion, absorption and reconstruction can this knowledge create greater value.
Artificial intelligence is likened to a person who has absorbed a lot of human knowledge, continuously studied deeply and evolved into a superior person. Artificial intelligence is inseparable from big data, and deep learning evolution is completed based on cloud computing platform.
Artificial intelligence is based on the support and collection of big data, which is applied to the specific performance and operation mode set manually. Big data is the accumulation of data such as continuous collection, precipitation and classification.
Compared with many previous data analysis technologies, artificial intelligence technology is based on neural network, and at the same time, multi-layer neural network has been developed, which can carry out deep machine learning. Compared with other traditional algorithms, this algorithm has no redundant assumptions (for example, linear modeling needs to assume the linear relationship between data), but completely uses the input data to simulate and construct the corresponding model structure. The characteristics of this algorithm determine that it is more flexible and can have self-optimization ability according to different training data.
However, this remarkable advantage has brought about a significant increase in the amount of calculation. Before the breakthrough of computer computing power, such an algorithm has almost no practical value. About ten years ago, we tried to use neural network to calculate a set of data that is not massive. Waiting for three days may not have the result. But today's situation is very different. High-speed parallel operation, 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 has no less influence on human beings than the Internet, and the power it releases will completely change our lives again.