Motahear Hossain’s Expanded Definition of Artificial Intelligence (AI)

TO: Prof. Jason Ellis.
FROM: Motahear Hossain.
DATE: 03/26/2021.
SUBJECT: Expanded Definition of Artificial Intelligence (AI).


The purpose of this 750-1000 Word Expanded Definition is to provide all the possible meanings of a scientific term, which is related to modern-day technology and associated with my college major. In this following document, I will be defining the term “Artificial Intelligence,” including the possible meanings and usages of that term. I will also explore the word history of this term, explain peculiarities of its uses, and offer examples of this term. To provide examples, I will address and discuss several definitions and quotations from verified sources and discuss, compare, and contrast those definitions and quotes from the different authors. Conclusively, I will provide my practical explanation of the term throughout this learning process.


According to the Oxford English Dictionary, the word “Artificial Intelligence” is a noun, connecting with two separate arguments, artificial adj. + intelligence n. They define “Artificial Intelligence” as “The capacity of computers or other machines to exhibit or simulate intelligent behavior; the field of study concerned with this” (American Psychological Association. (n.d.)). Based on this definition, the meaning of artificial intelligence is a computer or machine capable of presenting itself or work on its own and replicate a job called artificial intelligence.
In another source, the World Encyclopedia describes “Artificial Intelligence (AI)” as “Science concerned with developing computers and computer programs that model human intelligence. The most common form of AI involves programming a computer to answer questions on a specialized subject. Such ‘expert systems’ are said to display the human ability to perform expert analytical tasks. A similar system in a word processor may highlight incorrect spellings and be ‘taught’ new words. A closely related science, sometimes known as ‘artificial life,’ is concerned with more low-level intelligence” (Philip, 2014). Unlike Oxford English Dictionary, this is a broader approach of definition. Encyclopedias compare artificial intelligence with the human brain and designation it ‘artificial life.’ They state it will work by a set of programs and made for a specialized subject. It can provide the correct answer, detect the wrong answer, and suggest better options based on the system (AI) is working.


According to Rockwell Anyoha (August 28, 2017), “In the first half of the 20th century, science fiction familiarized the world with the concept of artificially intelligent robots. It began with the “heartless” Tin man from the Wizard of Oz and continued with the humanoid robot that impersonated Maria in Metropolis.” In his blog post, the writer wrote the history of the concept of artificially intelligent robots or robotic systems. Anyoha claims that Alan Turing was the person who saw the possibility of artificial intelligence. If humans can solve the problem and make the decision, Turing thought, why not a machine? Besides, blogger claims most scientists, mathematicians, and philosophers were optimized for the potential possibility of artificial intelligence around the turn of the twentieth century and started work on the program. It began with cracking the ‘Enigma’ code used by German forces during the Second World War. But as technology advances, earlier standards that defined artificial intelligence become outdated. These days the artificial intelligence (AI) is developing to benefit many different industries, so the meaning of artificial intelligence (AI) has become much broader.
In the article “Artificial Intelligence in the 21st Century” J. Liu et al. states that “Due to the historical development, AI has been utilized into several major subjects including computer vision, natural language processing, the science of cognition and reasoning, robotics, game theory, and machine learning since the 1980s.” (2018, p. 34403). As J. Liu et al. has indicated, artificial intelligence is not just defining a particular sector in the technology industry; nevertheless, it is much broader than we think. Nowadays, artificial intelligence is applying in every segment. For instance, computer vision of object recognition is the process of identifying the picture or object. Using computer vision, we can analyze any blurred images, read a map, or recognize substances like fingerprints. In the same ways for home and industrial security purposes, some companies use a security camera with installing facial recognition software. The same software can be used in a drone for shipping purposes or detecting criminal activities.
According to an article in the New York Times, “Police Drones Are Starting to Think for Themselves” Metz C. states that “In Chula Vista, drones are already an integral part of the way the police respond to emergencies. After an emergency call comes in, officers give the drone a location, and it flies to that point on its own — before returning on its own, too.” In the article, Metz also mentioned that Chula Vista is the first city in the world to use drones as first responders. Since the program began two years ago, Chula Vista police have used drones to respond to up to 15 emergency calls a day, totaling over 4,100 flights. This report suggests that artificial intelligence drones are now taking the place of human cops, and they are performing even better. This drone is a perfect example of artificial intelligence in action. It has the ability to deliberate and make decisions that are most likely to result in the achievement of a particular objective.


After going through all of the concepts, quotes, and learning from college courses, I have concluded that Artificial Intelligence is a clone of the human mind that is programmable as an algorithm and applied to machines to operate and run software without human intervention. If it can deliberate and take decisions that have the best chance of achieving a particular goal, it will be an ideal trait. Artificial intelligence would be advantageous to us in the future. It is something to be utilized in a wide range of industries and sectors.


American Psychological Association. (n.d.). Artificial intelligence. In Oxford English Dictionary. Retrieved February 19, 2021, from

Philip’s. (2014). Artificial intelligence. In World Encyclopedia. Retrieved February 19, 2021, from

Anyoha, R. (August 28, 2017). The History of Artificial Intelligence. Retrieved from

J. Liu et al. (2018). Artificial Intelligence in the 21st Century. IEEE Access, 6, 34403-34421.

Metz, C., (December 5, 2020). Police Drones Are Starting to Think for Themselves. The New York Times.

Summary of Chen et al.’s “Smart factory of industry 4.0: Key technologies, application case, and challenges”

TO: Professor Jason W. Ellis.

FROM: Motahear Hossain.

DATE: March 3, 2021

SUBJECT: 500-Word Summary of Article About Smart Factory.

This memo is a 500-word summary of the article, “Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges,” by Baotong Chen, Jiafu Wan, Lei Shu, Peng Li, Mithun Mukherjee, And Boxing Yin. This article discusses the latest of 4 distinct industrial revolutions that the world has or is currently experiencing.

According to the research, upgrading the manufacturing industry is a combination of advanced physical architecture and cyber technologies. Those technologies are constructed with three layers, including the physical resources layer, network layer, and data application layer. The researcher Chen et al. are examining those issues scientifically and try to find supplementary solutions with references. 

The traditional industry faces threats because of the rapid change in the technology sector. Currently, another advanced system is coming with integrations of computation, networking, and physical processes called the Cyber-Physical system. This system is capable of achieving advanced manufacturing systems with big data warehouses and cloud-based computing. Several studies (Benkamoun et al., 2014; Radziwon et al., 2014; Lin et al., 2016, p. 6506) found that to build a smart factory, manufacturing enterprises need to be more advanced in the production and marketing sector. It signifies a dive advancing from more outdated automation to a completely connected and flexible system. Research by Chen et al., suggests that there are still many technical problems that need to be solved in order to build a smart factory. An example of this would be the physical resources layer. The Modular Manufacturing Unit should be a self-reconfigurable robotic system with a configurable controller system, which will have the auto managing ability to take the action like extend, replace, and so on.

According to Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges (2018), “Morales-Velazquez et al. developed a new multi-agent distributed control system to meet the requirements of intelligent reconfigurable Computer Numerical Control (CNC)” (p. 6507). Which could utilize its system of control. Another important modular manufacturing unit is intelligent data acquisition. It includes data analysis, reporting, network connectivity, and a remote-control monitoring system. For using data acquisition, the most common wireless sensor network is RFID, ZigBee, and Bluetooth; However, Zhong et al. proposed an RFID-enabled real-time manufacturing execution system (Chen et al., 2018, p. 5608). According to researcher Zhong et al., this system is capable of making decisions and guarantee responses within specified time constraints. Also, the writer proposes to have a standard OPC UA-based interaction in multi-agent systems. With this system, multiple transport layers and a sophisticated information model allow the smallest dedicated controller to freely interact with complex, high-end server applications with real-time communication. 

Despite all of this, researcher Chen et al. has drawn attention to the fact that there are still some difficulties to build a smart factory. Like in order to have a self-reconfigurable robotic system, equipment must be smart manufacturing, and the industrial internet of things should be progressive.


CHEN, B., WAN J., SHU L., LI P., MUKHERJEE M., AND YIN B. (2018). Smart factory of industry 4.0: Key technologies, application case, and challenges. IEEE Access, 6, 6505-6516.