Artificial Intelligence
Artificial Intelligence 
https://www.datasciencecentral.com/profiles/blogs/artificial-intelligence-as-a-service-aiaas
Overview
Artificial Intelligence(AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans (techopedia, 2018). AI is a way of creating a computer-controlled robot, or a software which is equivalent in terms of an intelligent human mind. There are three types of AI: Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI) (Shevchenko, 2016). ANI is an artificial intelligence that is focused on one narrow task. Narrow Intelligence is found everywhere such as Google maps, Facebook suggestions, and mobile devices. AGI is defined as human level intelligence. It means that a machine is capable of thought on the same level as a human. AGI is very complex and difficult. It requires enormous computational power. ASI is capable of intelligence that exceeds that of a human. This type of AI has the capability to accomplish everything that a human can do and more. “Data Analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information” (Data Analytics , 2018). AI is important because it allows us to collect data on certain human behaviors to help us derive insights and essentially do a behavioral analysis.
Data Analytics Comparison
Data analytics and AI are a powerful combination. In the recent years, the advancement of technology has led to an increase in the volume of data that is being stored and collected. The purpose of data analytics is to collect both structured and unstructured data across the entire organization, which can be combined, compared and examined to find patterns and other useful business information. The volume of data can be so large that its difficult to process using a traditional database. To analyze large data, data analytics uses special software and applications for dimensional data modeling, data visualization, decision trees, clustering, data mining, and forecasting. Data analytics helps AI untangle solutions to problems by associating similar data for future use. Furthermore, data analytics allows AI to find proper information from larger data pools more rapidly and efficiently. As the amount of data increase, figuring out a way to contain it becomes a challenge.
Example
An example could be Google’s self-driving cars: it gathers data from its nearby locations in real time and process the information to make safe and smart choices on the road (Shevchenko, 2016).
References
Artificial Intelligence as a Service – AIaaS. (2017, October 19). Retrieved from https://www.datasciencecentral.com: https://www.datasciencecentral.com/profiles/blogs/artificial-intelligence-as-a-service-aiaas
Data Analytics . (2018, April 15). Retrieved from http://www.bhavnacorp.com: http://www.bhavnacorp.com/page_data_analytics.html
Shevchenko, T. (2016, August 10). 3 Types of Artificial Intelligence Everyone Knows About. Retrieved from http://letzgro.net: http://letzgro.net/blog/3-types-of-artificial-intelligence/
techopedia. (2018, April 07). Retrieved from https://www.techopedia.com: https://www.techopedia.com/definition/190/artificial-intelligence-ai
Tunikova, O. (2018, January 5). StopAd Blog. Retrieved from stopad.io: https://stopad.io/blog/artificial-intelligence-facts