If the standard by which to measure the explanatory value of a view were its revolutionary character, then Turing's (1936) analysis of the concept of computation would be highly valued indeed. Whereas the science of mind was once dominated by behaviorists, today it is dominated by computationalists. For computationalists, the mind/brain is a computer. As computationalists came to shoulder the burden for explaining how the mind/brain works, Turing's analysis of what counts as a computer became the standard by which to justify empirical claims about whether something is a computer. According to 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'.
The connection with the computing science is that in nowadays the algorithms are designed to be used by a machine. So algorithms can be expressed in more languages like natural language , Java, C++. The computer solves a problem by way of a computer program, which as it is mentioned above is a list of orders giving detailed instructions about the action of the computer. Algo... ... middle of paper ... ... way. It is true that people who using computers daily they do not understand these connection between mathematics and computer science.
By theoretical meanings theses hyper machines are just like turing machines, using abstract resources to manipulate or compute abstract objects including symbols and numbers. Therefore when someone claims that there exist a machine for a halting problem, then it means there is a theoretical machine exist instead of physical one. However the hyper computational resources are often physically praised and there is interest whether these machines are physically exist or not in theoretical way as well as in practice. Now I will represent the different models of hyper computing machines and presents resources that these machines used. Mine focus will be on mathematical nature of these resources.
Functionalists see the mind as a functional type with a major role of information processing, rather than the physical brain (113). Therefore computers in the future have the potential to realise this function and once they can, they can be considered to have a mind. To suggest that machines cannot think would take on a solipsist view, which could entail doubting the ability that anyone can think (113). Turing devises a version of the imitation game, where an interrogator questions one human and one machine (in separate rooms) and tries to determine which one is machine. If a machine can pass this test, then they can think (128).
The main objective of a NLP program is to understand input and initiate action. Definition: It is the science and engineering of making intelligent machines, especially intelligent computer programs. AI means Artificial Intelligence. Intelligence” however cannot be defined but AI can be described as branch of computer science dealing with the simulation of machine exhibiting intelligent behavior. History: Work started soon after
In contrast, "weak AI" approach focus instead on simulating intelligence (attempting to create machines which will be perceived as intelligent by their users) rather than trying to create it through a model of the mind. The field of Artificial Intelligence has split into several different approaches based on the opinions about the most promising methods and theories. These rivaling theories have lead researchers in one of two basic approaches: bottom-up approach (which believe the best way to achieve artificial intelligence is to build electronic replicas of the human brain's complex network of neuronsand) and top-down (which attempts to mimic the brain's behavior with computer programs).  Many articles showed a desire to allay fears that computers truly are intelligent, or worse, that human might soon be supplanted by machines.  Intelligent computers, robots, androids, and cyborgs have come to be staple characters in science fiction stories and films.
Specifically, in how the theory likens conscious intelligence to a mimicry of consciousness. In Alan Turing’s study of computing and consciousness, he developed the Turing Test, which essentially led to the notion that if a computing machine or artificial intelligence could perfectly mimic human communication, it was deemed ‘conscious’. REF. However, many do not agree and instead argue that while computers may be able to portray consciousness and semantics, it is not commensurable to actual thought and consciousness. Simulation is not the same as conscious thinking, and having a conscious understanding of the sematic properties of the symbols it is manipulating.
I-function and AI The idea of creative and intelligent nonhumans is at once exciting and extremely useful. Wouldn't it be great to have a computer assistant that could anticipate your needs, or come up with novel solutions on its own? Scientists have often compared the function of the nervous system to computer programming, but does this comparison translate to an actual causal relationship? The way physics describes communication between computer parts in a binary system remarkably resembles the communications between neurons in the body. When considering the brain, science only looks at the physical components.
For Peter Denning and Cohen and Haberman, computer science corroborates with the “scientific paradigm,” but for distinctive rationales: one as the embodiment of the use of the scientific method, the other as the embodiment of language. Neither of these views are wrong or even mutually exclusive; one could argue that computer science as a language is just a way to communicate the scientific method in a way that computers understand. To elaborate, scientists often construct systems which implement hypothesized information processes through computers and then correlate them with the real thing [Denning 2005]. This illustrates how computers in these studies are tools to test hypotheses, an essential part to the scientific method. In addition, language could even be seen as the personification of problem solving; without the articulation of issues, and the communication needed to solve them, attempting to settle issues would be inefficient, if not utterly impossible.
A new definition of knowledge including authenticity shows civilized humans compare to artificial intelligent objects. Even more, developed humans require both knowledge of form and content. Both form and content knowledge must maintain balance, which is intimacy on humans. Technology makes people to think simply and advanced technology develops smart artificial objects like humans. Even though there are artificial smart “humans,” they cannot express their own knowledge without computer coding, and machines specifically own mostly content knowledge, unlike real humans.