Machine Learning
Introduction
It could be argued that machines learning is influencing the way we perceive information and think. From customer service software to Google search, machine learning is already becoming a daily phenomenon that is aiding us make better and faster decisions. Machine learning is best defined as an artificial intelligence approach in which machines are allowed to learn and further make decision about certain outcomes without programming it to. In this paper I will further define what machine learning is and by using Facebook’s Messenger Platform as an example, I will showcase how machine learning is being implemented in our everyday life.
What Is Machine Learning? From a technical perspective, machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experiences without being explicitly programmed (N.A 2017). Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves (N.A 2017). Unlike human learning, machine learning is based on algorithms.
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This tool gives companies the power to have better customer service and foster a relationship with the company, brand or business. More so, Facebook has also opened the chatbot to developers. Researchers at Facebook Artificial Intelligence Research (FAIR) have open-sourced code and published research that provides developers new dialog agents (Lewis 2017). The availability of the code will give developers the resources needed to build more complex bots that can decipher meanings and continuously learn to get better over time (Lewis 2017). This can also help companies give their customers a more unique experience and provide an overall better branding practice for the
The companies like Google have the idea that they know what an individual likes from the information the users submit. The primary challenge, in this case, is that social media users are seen as incapable of making rational decisions about their choices. For example, on may be walking down a street during lunch hours and from nowhere, they get a notification that there is a restaurant in their surrounding that is offering a certain meal during those times. Moreover, Jacob Silverman asks the question as to why social
This world of artificial intelligence has the power to produce many questions and theories because we don’t understand something that isn’t possible. “How smart’s an AI, Case? Depends. Some aren’t much smarter than dogs. Pets. Cost a fortune anyway. The real smart ones are as smart as the Turing heat is willing to let ‘em get.” (Page 95) This shows that an artificial intelligence can be programmed to only do certain ...
Artificial Intelligence (AI) is one of the newest fields in Science and Engineering. Work started in earnest soon after World War II, and the name itself was coined in 1956 by John McCarthy. Artificial Intelligence is an art of creating machines that perform functions that require intelligence when performed by people [Kurzweil, 1990]. It encompasses a huge variety of subfields, ranging from general (learning and perception) to the specific, such as playing chess, proving mathematical theorems, writing poetry, driving a car on the crowded street, and diagnosing diseases. Artificial Intelligence is relevant to any intellectual task; it is truly a Universal field. In future, intelligent machines will replace or enhance human’s capabilities in
One of the hottest topics that modern science has been focusing on for a long time is the field of artificial intelligence, the study of intelligence in machines or, according to Minsky, “the science of making machines do things that would require intelligence if done by men”.(qtd in Copeland 1). Artificial Intelligence has a lot of applications and is used in many areas. “We often don’t notice it but AI is all around us. It is present in computer games, in the cruise control in our cars and the servers that route our email.” (BBC 1). Different goals have been set for the science of Artificial Intelligence, but according to Whitby the most mentioned idea about the goal of AI is provided by the Turing Test. This test is also called the imitation game, since it is basically a game in which a computer imitates a conversating human. In an analysis of the Turing Test I will focus on its features, its historical background and the evaluation of its validity and importance.
As our world expands through the growing abilities and applications of computers in our everyday lives, it seems that the role of the computer has been reversed. Before we knew that the computer only understood what we programmed it to understand; however, now the majority of our society is learning more from computers than they are able to input into it. Dumm (1986 p.69)
This is the reason why a giant like McDonald’s, which spends millions of dollars on advertisements and promotions, has collaborated with WeChat to offer discount coupons, and services to its customers. This trend of cross-promotions is going to increase in the coming future. The focus would be to increase revenues and profits, but social messaging app makers such as Tencent need to remain true to their vision and goals. WeChat must remain simple, free to download, provide exceptional user interface, and introduce better features in days ahead.
Chat-bots programmed with Artificial Intelligence such as Slack can store a lot of data and produce it later for future reference. Apple’s SIRI and Microsoft’s Cortana are already being used to do menial tasks and set reminders for days far into the future.
In order to see how artificial intelligence plays a role on today’s society, I believe it is important to dispel any misconceptions about what artificial intelligence is. Artificial intelligence has been defined many different ways, but the commonality between all of them is that artificial intelligence theory and development of computer systems that are able to perform tasks that would normally require a human intelligence such as decision making, visual recognition, or speech recognition. However, human intelligence is a very ambiguous term. I believe there are three main attributes an artificial intelligence system has that makes it representative of human intelligence (Source 1). The first is problem solving, the ability to look ahead several steps in the decision making process and being able to choose the best solution (Source 1). The second is the representation of knowledge (Source 1). While knowledge is usually gained through experience or education, intelligent agents could very well possibly have a different form of knowledge. Access to the internet, the la...
Social networking, such as Facebook and Twitter, is a great tool for people to communicate, but it also leads to less face-to-face communication. Face-to-face discussions are the foundation of human communication that allows us to build trust and clearly
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...
Let me begin with one of the major theories concerning the philosophy of artificial intelligence: The Church-Turing thesis. The Church-Turing thesis is the brainchild of Alan Turing and Alonzo Church. It concerns the concepts of “effective” and “mechanical” in logic and mathematics. Both Turing and Church reached the hypothesis independently and in different forms. But both forms confront similar issues and the general form is known as the ‘Church-Turing thesis’. In general, the thesis asserts that a machine can execute all processes that are ‘mechanical’[1]. Clearly, there is some ambiguity in this statement. What is meant by mechanical? What is meant by machine?
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?
Data mining has four stages: collection, aggregation, interrogation and prediction (de Zwart et al 2014, p. 715-719). As with filtering, this process more often than not happens without the knowledge of users and regardless, it is “almost impossible” to prevent (p. 716). The importance of user consent has already been touched upon, as has the implications for the balance of power between social media platforms and the users. As social media implicitly exists for users to interact with one another , for the power to remain out of the hands of the users is especially problematic as it in many ways contradicts the supposed purpose of social media (Baym 2015, p. 1-2). More specific to data aggregation and interrogation, the power imbalance works against the freedom of expression and instead restricts the ability of the individual to control their own identity and the way it is presented. Data aggregation, or the collection of data over time, has no way or retaining context for specific actions or interactions (de Zwart et al 2014, p. 716). The previously discussed context collapse comes into play once more, as the way a individual may present themself in interactions with various other users may form what appears to be contradictory information. The interrogation of this data then becomes the
Some machine learning works in a way similar to the way people do it. Google Translate, for example, uses a large database of text in a given language to translate to another language, a statistical process that doesn 't involve looking for the "meaning" of words. Humans, do something similar, in that we learn languages by seeing lots of examples. Google Translate doesn 't always get it right, precisely because it doesn 't seek meaning and can sometimes be fooled by synonyms or differing connotations. (Schapire, 2008) Current and future examples of machine learning include; optical character recognition, face detection, spam filtering, fraud detection, weather prediction and medical
Artificial Intelligence “is the ability of a human-made machine to emulate or simulate human methods for the deductive and inductive acquisition and application of knowledge and reason” (Bock, 182). The early years of artificial intelligence were seen through robots as they exemplified the advances and potential, while today AI has been integrated society through technology. The beginning of the thought of artificial intelligence happened concurrently with the rise of computers and the dotcom boom. For many, the utilization of computers in the world was the most advanced role they could ever see machines taking. However, life has drastically changed from the 1950s. This essay will explore the history of artificial intelligence, discuss the