USING ARTIFICIAL INTELLIGENCE IN BIG DATA


This article starts by explaining what is AI (Artificial Intelligence). It explains is by saying that AI is the level of a machine’s intelligence compared to a natural intelligence, showed by human beings and animals. Intelligence is taught to a machine to make it perceive the enviroment and act to achieve some goals successfully. Sometimes, Artificial Intelligence is also called Machine Intelligence. After the brief explanation about AI, the article starts to discuss about how can a machine be taught.

Basically, the way we can teach a machine is using codes. We can write codes in programming language so the machine can understand the meaning of those codes and can learn from it. These machines are also programmed to generate their own codes, so it can start learning by itself and start to improve itself. So, in general, machines are taught by programming language codes that the machine can understand. These codes teaches the machine to do something to achieve a certain goal, and the machine is also programmed to use its basic codes to create new codes and keep improving itself and learning more and more when it feels the workload is too high.

The machines are made to work on problems humans have a lot of difficulty dealing with. Machines assists us since a long time ago, since the use of Abacus. However, now that technology evolved, there is no limit to the amount of information that a machine can deal with.

After this, the article starts talking about Big Data. They explain that Big Data is what the name says, large amount of data that can be understood by and stored in a machine. And they also say that the best way of dealing with Big Data is with AI. We have a lot of data available online and when this data is used properly, it can give us a lot of meaningful insights about the industry that the data belongs.

The article also lists some ways companies are applying artificial intelligence and big data, such as natural language processing, helping agricultural organizations and corporations broaden their monitoring capability, helping banking and securities monitor financial market activities, among others.

Finally, the article brings its Final Thoughts. They say there are huge investments in the use of AI in Big Data analysis for the benefit of all. It is said that the possibility of increasing the predictability of certain events allows us to change our approach to how everything is done.

Name: Erick陳高
ID: D0766156

Comments

  1. Ivy LeeJune 17, 2020 at 8:16 PM

    Big data is a powerful calculation. It does not take action based on the results, but only seeks results. It defines a very large data set. Artificial intelligence is about making decisions and learning to make better decisions. Although they are very different, artificial intelligence and big data still work well together. This is because artificial intelligence needs data to build its intelligence, especially machine learning.


    In recent years, the application of artificial intelligence technology in various industries has been applied. In those industries, artificial intelligence provides a new method for the economic development. The rapid development of artificial intelligence is inseparable from the support of big data. In the development of big data, the artificial intelligence has also enabled more types and larger amounts of data to be processed and analyzed quickly.

    Nowadays, most of the achievements of artificial intelligence development are closely related to big data. Through data acquisition, processing, analysis, and then from the massive data to gain valuable insights, to provide materials for more advanced technologies.

    D0773626

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  2. Paul LiJune 26, 2020 at 8:37 AM

    This article really highlights the importance of big data and shows why currently big data which is itself is Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. When we handle big data, we may not sample but simply observe and track what happens. Therefore, big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value and i really that articles like this highlight the usefulness and endless possibilities that big data provide, not only in this day and age but for the future aswell.

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