Natural Language Processing
To digest natural language implies understanding, a function that is uniquely human. To understand something implies to have senses that interpret the world such as emotions and awareness of our own physical experiences. When someone tells a story, we rely upon previous experience for interpretation. We form a reaction, our heart rate may change, we may start sweating, we may relax or tense, and feel certain emotions such as fear. Upon getting new information, a persons attitude may change or the way they think may change. A computer made of metal simply does not have the faculties to experience the world as we do. It can be programmed to respond in such a way that mimics a human response, but can not be considered to be really understanding what it is doing. Recall the story of Helen Keller, how she finally began to learn a language when she was given immediate experiential feedback. The teacher would pour water on her and then do the sign language for the word in her hand. The founder of Toastmaster's organization started it on the premise that people learn in moments of pleasure, and structured the organization so it would provide just that. A computer would not have the senses to make such understanding of these words and experiences possible.
In addition to its lack of cognitive ability, a computer can not form expectations based upon a situation. A political speech can be very serious, but when seen on Saturday Night Live, it will be interpreted as funny. A similar problem is the extra meaning conveyed by the tone of voice or body language. We could always program an exhaustive data bank with all the different possibilities of input, but the system as we know it could not search all of these within a reasonable period of time, nor could it adapt to future changes. One of the problems with natural language processing systems is that humans themselves are often not very good natural language generators or processors. We often apply our own bias and expectations to what we hear. Two people can make eye contact and set up a whole series of background such that they now what each other are talking about. That very fact may be a bonus for computer natural language processing because we can predict with certainty how the system will interpret the information and therefore have greater clarity than people.
1. What is the name of the document? Ida Tarbell Criticizes Standard Oil (1904) 2. What type of document is it? (newspaper, map, image, report, Congressional record, etc.)
Andy Clark strongly argues for the theory that computers have the potential for being intelligent beings in his work “Mindware: Meat Machines.” The support Clark uses to defend his claims states the similar comparison of humans and machines using an array of symbols to perform functions. The main argument of his work can be interpreted as follows:
Human conversations are too complicated for machines to understand and interact properly without flaws. This is what separates humans from animals. Even the dumbest man will be able to form sentences and converse with other human beings, while even the smartest animals will never be able to.... ... middle of paper ... ...
From the moment that we are born, we are exposed to means of language and communication. Though technically we can not speak as babies; we give our parents small signals to let them know what we need such as, being hungry or needing a diaper change. Language is proven to be essential and an important part of life. In the essays, Homemade Education, by Malcolm X and Spanish Lessons, by Christine Marin both essays give a strong example of why language is important. In Malcolm’s essay, he explains how when he was prison the power of language completely changed his life. In Marin’s essay she talks about her experience with the English and Spanish language and how both languages opened up new doors for her in her life and
Carr starts off his argument by referencing a “2001 a space odyssey” released in 1968 about a computer named HAL that tries to kill the astronauts that are on the spaceship that HAL controls. Carr uses an excerpt from this movie to incite fear into his readers and fear clouds judgement and causes irrational ideas to be formed. This movie is an over exaggerated sci-fi thriller and not a realistic representation of what computers are becoming. At the conclusion of his argument Carr does not forget to leave his readers the way he greeted them, Carr quotes 2001: a space odyssey “i can feel it. I’m afraid” (Carr 328). Although emotions are a strong way to engage with a reader, strong emotions also distract readers from the actual argument and encourage the reader to make a decision based on their feeling rather than their actual brain. The fact that Carr uses emotion to convince his readers is quite ironic, considering he is arguing that new technology is limiting our ability to use our brains. In contrast Thompson’s article uses logic and reason to make his argument. At the same time Thompson’s article still engages readers and is just as interesting to read as Carr’s essay. Thompson’s article starts off pondering whether computers or humans are better at chess. To answer this
So you think that programing is different than learning. You might think the same as my grandma that programing is something where things are just drilled into you like people who are members of cults. Well when your teacher stood over you desk in elementary and do drilled you on the multiplication tables was that not programming? Would you know that 1x5 does not equal 10 if everyone you ever met said that it did. Another argument my grandma used was my little cousin and how when he runs into a wall he learns that it hurts so he doesn’t do it again. (Well actually he does it because he has a hard head). Yet a professor in Calgary builds robots that do not even contain a microprocessor yet it can learn. He builds them out of spare part from broken electronics such as walkman’s.
...e and codes. With the continued advancement in computer technology, this entire argument though seemingly convincing, may in the future become a mute point. It is interesting that this argument has generated so much interest over the years. Undoubtedly, this argument is not with without fault yet, it still stands to substantiate beliefs that computers are not cognitively independent.
The traditional notion that seeks to compare human minds, with all its intricacies and biochemical functions, to that of artificially programmed digital computers, is self-defeating and it should be discredited in dialogs regarding the theory of artificial intelligence. This traditional notion is akin to comparing, in crude terms, cars and aeroplanes or ice cream and cream cheese. Human mental states are caused by various behaviours of elements in the brain, and these behaviours in are adjudged by the biochemical composition of our brains, which are responsible for our thoughts and functions. When we discuss mental states of systems it is important to distinguish between human brains and that of any natural or artificial organisms which is said to have central processing systems (i.e. brains of chimpanzees, microchips etc.). Although various similarities may exist between those systems in terms of functions and behaviourism, the intrinsic intentionality within those systems differ extensively. Although it may not be possible to prove that whether or not mental states exist at all in systems other than our own, in this paper I will strive to present arguments that a machine that computes and responds to inputs does indeed have a state of mind, but one that does not necessarily result in a form of mentality. This paper will discuss how the states and intentionality of digital computers are different from the states of human brains and yet they are indeed states of a mind resulting from various functions in their central processing systems.
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...
In this essay I intend to investigate how differently one of the closed word classes, determiners, are approached in a series of pre and post corpus-based English grammar reference books, course books and practice books. And the theme of my investigation is how corpus affects the development of English teaching materials. The grammar reference books I intend to analyze and compare are “A Comprehensive Grammar of the English Language” (ACGEL) and “Cambridge Grammar of English” (CGE). The former is an indispensable grammar reference book first published in 1985, which has been widely consulted in researches in relation to English linguistic studies, while the later offers clear explanations of both spoken and written English grammar based on authentic everyday usage.
The Features of Written Language and Speech In English language there are two different ways of actually presenting language. These are written language and speech. These two factors of speech both include many different features between themselves. These features are mostly opposite to each other as they are completely different ways of presenting language. Written language is structured into paragraphs unlike general speech which is hardly thought about before being said and is flowing naturally.
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
In addition, emotions can be only transmitted by the human brain and cannot be programmed into a computer. One of the reasons is there are too many emotions to be described and they can be a mixture of feelings that it would be hard to put it into one category. Furthermore, the computer wouldn’t have the ability to know to what situation he should apply certain emotion. And different emotions can be applied to the same situation; it all depends on the experiences in our past. Emotions are personal and are different for every person and it would have to be different for every computer.
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?
Word Processing is using a computer to create, edit, and print documents. Of all computer applications, word processing is the most commonly used. To perform word processing, a computer, a special program called a word processor and a printer are required.