The Language of Machines
Computers are language machines. By saying this I mean both that language processing is a valuable metaphor for understanding computer computation and that, in a fundamental way, computer computation is language processing; no more, no less. The language understood by a modern computer when it first comes off the assembly line is quite simple. The alphabet of this language consists of two letters, 0 and 1 (or a and b or any other two characters, it doesn't matter), which is stored internally as two intensities of an electrical signal (either high or low). The grammar of this language has two rules: (1) Sentences consist of one word and (2) Words are all of a single specified length (probably either 16 or 32 characters). This computer knows in two ways. It knows what every word in the language means (i.e., what action to perform upon reading that word, information which is stored in the design of the processor), and it knows all of the words it has stored in memory. Each time a computer reads a sentence (executes a command), a change results in memory, dependent on what the sentence says and what is already in memory.
Modern computers are Turing machines (named after the British mathematician Alan Turing), which means that they are language machines which can simulate other language machines. In other words, given a special type of text to read (a program), a Turing machine that understands the simple language described above (for example) can act as if it understands a much more complicated language. This is why modern computer keyboards have more than just 0's and 1's on them. A modern computer comes complete with many virtual computers built on top of it, so to speak, enabling the computer to understand much more complex (although mathematically equivalent) higher-level languages. These are mathematical languages, of course; they have much more rigid structure and precise meaning than natural languages. They lack in many ways what Derrida calls "play." But must they? Is there an intrinsic fundamental difference between mathematical and natural languages, or is the difference instead that we have more control over mathematical languages because we know their rules and can understand the system in which they work, while with natural languages we know neither, because we are not in conscious control of their creation and we can not fully grasp how they operate in society and in our heads?
The official foundations for "artificial intelligence" were set forth by A. M. Turing, in his 1950 paper "Computing Machinery and Intelligence" wherein he also coined the term and made predictions about the field. He claimed that by 1960, a computer would be able to formulate and prove complex mathematical theorems, write music and poetry, become world chess champion, and pass his test of artificial intelligences. In his test, a computer is required to carry on a compelling conversation with humans, fooling them into believing they are speaking with another human. All of his predictions require a computer to think and reason in the same manner as a human. Despite 50 years of effort, only the chess championship has come true. By refocusing artificial intelligence research to a more humanlike, cognitive model, the field will create machines that are truly intelligent, capable of meet Turing's goals. Currently, the only "intelligent" programs and computers are not really intelligent at all, but rather they are clever applications of different algorithms lacking expandability and versatility. The human intellect has only been used in limited ways in the artificial intelligence field, however it is the ideal model upon which to base research. Concentrating research on a more cognitive model will allow the artificial intelligence (AI) field to create more intelligent entities and ultimately, once appropriate hardware exists, a true AI.
Turing's analysis of the concept of computation is indisputably the foundation of computationalism, which is, in turn, the foundation of cognitive science. What is disputed is whether computationalism is explanatorily bankrupt. For Turing, all computers are digital computers and something becomes a (digital) computer just in case its 'behavior' is interpreted as implementing, executing, or satisfying some (mathematical) function 'f'. As 'computer' names a nonnatural kind, almost everyone agrees that a computational interpretation of this sort is necessary for something to be a computer. But because everything in the universe satisfies at least one (mathematical) function, it is the sufficiency of such interpretations that is the problem. If, as anticomputationalists are fond of pointing out, computationalists are wedded to the view that a computational interpretation is sufficient for something to be a computer, then everything becomes a digital computer. This not only renders computer-talk vacuous, it strips computationalism of any empirical or explanatory import. My aim is to defend computationalism against charges that it is explanatorily bankrupt. I reexamine several fundamental questions about computers. One effect of this computation-related soul-searching will be a framework within which 'Is the brain a computer?' will be meaningful. Another effect will be a fracture in the supposed link between computationalism and symbolic-digital processing.
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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.
Adolf Hitler was a Nazi German Leader who attempted genocide and was part of one of the worst wars, WWII. Hitler took up the role of initiating the Holocaust which ended up In the death of numerous Jews.
In this essay, I describe in detail a hypothetical test contemporarily known as the Turing test along with it’s respective objective. In addition, I examine a distinguished objection to the test, and Turing’s consequential response to it.
The processor is the factory floor of the computer; it’s recipient of all the instructions and then processes them. It conveys the instructions of a computer program by performing rudimentary arithmetical, logical, and input/output operations of the system.
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 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.
A computer is an electronic device, operating under the control of instructions kept in its own memory. The computer can accept and process data according, then it produce and save the results for future use (Gary B. Shellly 2012). In short, computer is devices that use to process information. In the help of computer, data or raw fact (input) can be transform into useful information (output).
In this essay, you will read about the way a computer works including hardware, software and history regarding a computer. A computer is a devise that processes, organize, displays information, and calculates. It can communicate with other computers all over the world. Computers can perform thousands of billions of calculations per second. Computers are used for business, bar codes, track inventories, home use, school work, and studies among other things. Computers can produce several things at once, for example: information, images, numbers, movies and sound. This is why every part of a computer is important when it comes to managing the system.
Another difference between the human brain and the computer is, the creativity of the human brain. For instance humans can create art, act in plays, or write stories and songs but computers can only help us in these activities not come up with them. While computers can help us solve math problems and find answers to certain questions it can never think of new solutions until they have been programmed into them. Furthermore computers cannot create new games or produce anything they desire like humans.
A computer is a combination of several parts. These parts are Random Access Memory (RAM), a Central Processing
A computer is a device that has the capability of storing its own memory by operating under the control of instructions. This then enables the computer to accept data, which is also known as inputting information. To follow this, the computer then processes specified rules according to the data. The next action the computer takes is to generate results. This action is also referred to as output. Lastly, the computer stores the information for use at a later time. This is also known as storage.
Processors were originally any machine that could do logic and arithmetic functions. Processors are essential for computers because it executes commands and runs computer programs in order for a computer to operate. These chips convert input data to output information in the Central Processing Unit or as it is normally called, CPU. The Central Processing Unit executes instructions stored by programs. The Central Processing Unit interacts with main memory to access data and instructions. Although processors manage a lot of data in the computer, they can only store the data temporarily. Every instruction that the Central Processing Unit processes is depicted by a sequence of numbers. The numbers that represent the demanded action are stored in the Central Processing Unit’s temporary memory once ...