Artificial Intelligence Concepts : The Future Of AI

In Minds, Brains, and Programs, John Searle provided various counterarguments to the proposition that strong artificial intelligence is similar to human cognition and that machines are able to have similar cognitive experiences as humans, such as having intentions, as long as it has the right program. The purpose of this article was to demonstrate opposing approaches, which outlined that the theory of strong AI is flawed. The author did this by providing examples of how to disqualify the support for the theoretical perspective that machines, even though they have the appropriate programming, still cannot understand as humans do. Through various explanations and replies to the arguments, Searle makes his point and give examples of the promises.

In this paper I will consider John Searle's Chinese Room argument against Strong AI, and then explain how Paul Churchland's Luminous Room argument successfully opposes it. Strong AI is the proposition that intelligence is simply the formal manipulation of symbols, which is something that digital computers have. A digital computer is any machine whose states can be known and predicted by a machine function table that rationally gives future states and outputs from current states and inputs. Searle produces a reasonable and convincing argument against the claim that digital computers can have intelligence using his thought experiment, and does not run into any obvious or completely argument-ruining objections. However, his argument is most helpless

From this point, the book takes us away from believing that we can create intelligent machines with human-like intelligence. Nonetheless, while reading the book, I

The definition of intelligence has strongly been debated over for many centuries, and many individuals have their arguments for what it is. So what is really the true meaning of intelligence? Some, such as college professor of psychology, Carol S. Dweck, strongly believes that intelligence is something achieved through large amounts effort and having optimistic mindsets as inferred in her article, “The Secret to Raising Smart Kids”. However, on the other hand, successful author of best selling novel “Steve Jobs”, Walter Isaacson, claims that intelligence is an abstract idea that is derived from ingenuity and applying creativity to life and other material concepts. With almost completely opposite sets of beliefs, it is likely that Dweck will not agree with Isaacson’s nation of intelligence being derived from natural intuition rather than raw intelligence.

Weak AI is the understanding that computers are only useful in things like psychology or grammar. The great difference is that weak AI makes no claim that computers actually “understand” or are intellectual. The Chinese

Artificial Inelegance topic has captivated the minds of researches and common people alike. The use of AI comes into being as to try to understand our own brain and create a thinking machine. To begin the topic, one must explain of john Searles arguments against what he calls StrongAI. Searles creates a distinction between Strong Ai and Weak AI. While he has no issue with Weak Ai which is the idea of computers that assist us in crunching numbers based on our inputs

Being alive is to give yourself a meaning to life. To make judgements and think. Everything is parallel to this, because before consideration is made as to what it means to be alive, you must define the exact opposite. Only a thinking being is able to do that. A living person or AI is one capable of giving its own meaning to the universe or society, as well as its own interpretation of alive and dead. All object are dead otherwise without consciousness. Computers have seem "mind-like" to people since they were invented in 1950s. In the early days they were widely called "electronic brains" for their ability to process information. But the similarity between computers and brains isn't just superficial: at their most fundamental levels, computers and brains process data in a similar binary fashion. Whereas computers use zeros and ones to store and manipulate data, the neurons in our brains transmit information in binary, on/off spikes known as action potentials. This basic similarity is what underlies the burgeoning field of computational neuroscience, which hopes to understand how neuronal networks give rise to processes like memory and facial recognition so that they might be replicated in intelligent machines. But artificial intelligence has progressed slower than many had initially hoped. Yes, AI may have solved the game of checkers, but this is a far cry from being able to simulate consciousness. The central problem remains: we have no real understanding of how the brain gives rise to the mind, of how neurons and action potentials create

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

Nonetheless, French (2012) argues that the time has come to re-examine the abandonment of the idea that a machine programmed could pass the Turing test with unconditional accomplishments. Namely, new discoveries in intellectual cognitive science that have demonstrated that human intelligence is fundamentally linked to the embodied experience suggest that computers cannot imitate human intelligence in those aspects in which it is momentously dependent of the sensory experience of the world. Due to these discoveries, scientists abandoned the idea that computers would be able to fully emulate human behavior. However, as French (2012) suggests advances in information technology have brought about software that can collect and retrieve virtually all data that is presented about human experience on the internet. He cites a recent experiment in which a home camera system filmed the first 2 years of one baby’s life the entire time (French 2012). The data used to teach the computer about those aspects of human cognition as well thus facilitating it effusively to pass the Turing test. What remains is to ask whether a computer that could do that is in any imperative aspect different from a human (French 2012). French (2012) seems to be suggesting that passing this full version of Turing test

In attempting to answer the question of whether machines are able to think, Turing redesigns the question around the notion of machines’ effectiveness at mimicking human cognition. Turing proposes to gauge such effectiveness by a variation of an ‘imitation game,’ where a man and a woman are concealed from an interrogator who makes

In “Can Computers Think?,” John R. Searle argues that strong artificial intelligence is false and therefore machines cannot think or exhibit understanding like a human mind. Strong AI claims that a correctly written program running on a machine functions as a mind and there are essentially no differences between the software exactly emulating the actions of the brain and the mental contents of a human. Searle uses a thought experiment called the “Chinese Room Argument” to argue against strong AI. Various objections, such as the Robot Reply, challenge Searle’s argument by further testing the potential of a machine to possess understanding, intentionality, and subjectivity. In this essay, I will argue that Searle’s argument against strong AI

Through this, Searle argues that if a human and machine receive the same input and then respond by the same output, how are they any different from one another? When given the same purpose, humans and machines have the same response, therefore machines may have a mind. Gilbert Ryle created The computational theory of mind that claims “Computers behave in seemingly rational ways; their inner program causes them to behave in this way and therefore mental states are just like computational states”. He continues on by saying that “If logic can be used to command, and these commands can be coded into logic, then these commands can be coded in terms of 1s and 0s, therefore giving modern computers logic. Through this, how is one to tell if robots don’t have minds if they use logic just like humans do. When the purpose of humans and machines are the same, they may process differently in order to complete that purpose, although they may have the same output. Because humans and machines receive the same input and return the same output, they both have minds in addition to functions and processes in order to do that.

The attention is finally turned to this articles subject title,Google. The chief executive, Eric Schmidt says Google is “A company founded around the science of measurement…” (740) The creators admit to wanting to develop “the perfect search engine” or something as smart as people if not smarter. Carr mentioned the fact the creators believed “humans would be “better off”. Furthermore, they would like to they would like to build artificial intellegance on a large scale. This leaves Carr with an “unsettling” feeling. He makes his point by saying, “It suggests a belief that intelligence is the output of a mechanical process, a series of discrete steps that can be isolated, measured, and

For years, Artificial Intelligence has posed the question, what it means to be human, and more specifically the nature of consciousness. When confronted with the issue of the relationship between the mind and the body, the most likely argument is that both exist independently of each other but have a two-way relationship. However, recent advancements in machine learning, the technical algorithms that make up artificial intelligence, have suggested that this is not true. It is important to explore whether artificial intelligent agents are really capable of having these “minds” to achieve consciousness, even when they are built of physical components, such as codes. Up to this point in evolution humans are the only ones to achieve consciousness, however recent progression in artificial intelligence provides the possibility to prove otherwise. Consciousness must be defined with the possibility of bringing forth different theories. Defining consciousness and the relationship between the mind and material body will not only teach us more about artificial intelligence, but more importantly about the human condition and implications on personhood. One example of this would be AlphaGo, an artificial intelligence program built by Google that beat the world champion, Lee Sedol, in the Chinese game of Go. The game is said to demand high-order thinking and intuition to master  it, both of which require a mind ,  as there are trillions of potential moves possible, with the most optimal

Artificial intelligence, or AI, is a field of computer science that attempts to simulate characteristics of human intelligence or senses. These include learning, reasoning, and adapting. This field studies the designs of intelligent