MIS 2502: Data Analytics
Artificial Intelligence
Artificial Intelligence came into existence in 1956, which would later go on to be included in the Golden era time period. This was a time (1956-1974) where not many believed that intelligent machines would be possible at all. Due to the optimism expressed by researchers, AI has reached great lengths today in respect to data volumes, algorithms as well as computing power and storage. Status quo and in the next close few years to come, the projected growth rate of “smart capabilities” are projected to guide society past the normal range of the self-service era (Henschen). No longer do we have to perform automated tasks manually but now we are able to do so more accurately without fatigue through high volume computers ( sas.com).
In Data Analytics, we learned R, which is a software that acts on added intelligence. Similar to R, AI cannot be sold as a separate application. Instead, the products that we have, and use can be improved through AI’s capacity (sas.com). For example, “Siri” through apple is an application of added intelligence to iPhones software.
The incredible accuracy that is exhibited through AI’s deep networks makes technology such as Siri and Alexa possible. These AI models are programmed to adapt when presented with new data. This technique is called “Back Propagation” which lets the duplicate accommodate the added data if the initial answer is not quite right. Over a short time, these systems become more and more accurate as they are implemented more(sas.com).
Works Cited
“Artificial Intelligence – What It Is and Why It Matters.” – What It Is and Why It Matters | SAS, www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html.
Henschen, Doug. “How ML and AI Will Transform Business Intelligence and Analytics.” ZDNet, ZDNet, 10 Jan. 2018, www.zdnet.com/article/how-machine-learning-and-artificial-intelligence-will-transform-business-intelligence-and-analytics/.