Artificial Intelligence refers to the development of machines or computers with human-like capabilities in executing activities. The various technologies towards machine development are to ensure computers have the potential to act and think like contemporary human beings. Other scholars argue that artificial intelligence refers to a case in which a machine shows or is characterized to have human-related qualities working as a normal brain. Therefore, the impact of artificial intelligence quality is based on the extent to which activities or legal actions have a capability for achieving a certainly given objective. In most cases, artificial intelligence is presumed to be anything related to robotics (Lu 375). Most technologies, such as movie making, comprise human-like oriented machine actions. Artificial intelligence has a vast number of applications, such as in developing web-automated crawlers, industrial robots, automated processing systems, autonomous vehicles, among other essential fields. The paper focuses on artificial intelligence etymology, where Stephen Wilson describes artificial intelligence research as art while Nora Khan describes the importance of seeing, naming, and knowing of artificial intelligence in making life better.
The goal of Artificial Intelligence
The main goal of artificial intelligence growth is to address factors such as observation, thinking, and picking up. With the advancement in technology, it is essential to consider the earlier synthetic intelligence forms which have been recently deemed obsolete. Considering the previous approaches forming AI basics plays a significant role in determining the complete development path and also makes predictions on artificial intelligent growth (Lu 375). Most companies are continually developing a vast range of ventures to achieve maximum profits in production. By considering how human being interacts, think, and behave, it is possible to transfer the intelligence into machines by customizing them to assume human characteristics. The idea of artificial intelligence can be reflected in 1956, as stated by John McCarthy during his first meeting to establish the subject (Small 19).
Developing artificially intelligent systems was not simple, and neither did achieving the artificially intelligent being either. Following reports about the field, government funding dropped. The stories were criticizing the application and progress made in AI. These occurred between 1974 to early 1980, and it was termed as "AI winter" (Small 19). The field revived in the late1980s after the British government sided with the Japanese to fund and indulge in the system.
Another winter occurred between 1987 to 1993 as the market for the early generated computers dropped (Wilson 171). The correlation graph between AI and the old general-purpose computers was attributed to the decreased funding by the government. Another revival in the AI field embarked in the late 1990s (Wilson 171). Research in the area continued in 1997, and a spectated win in the field was evident. Russian chess grandmaster Garry Kasparov was defeated by an AI program named IBM Deep Blue (Small 19). The revelation led to a series of events that enabled a significant boom in the field. In 2011, another AI program named Watson defeated quiz masters, Brad Rutter and Ken Jennings, and won the Jeopardy show.
The current feature implemented in the AI field is implementing talking bots. AI judges were tricked to believing the "chatbot" was a real-skinned robot during its Turing test. A Turing test was developed in 1950 by Alan Turing and helped to estimate the intelligence of a machine (Small 19). However, critics and most experts say that the Turing test is not the best method to measure artificial Intelligence (Small 19). This is because the chatbot was able to dodge some questions during the test. The critics say that the Turing test is imperfect as it looks at the external behaviors of a machine. The test should be upgraded as the field is dynamic and ever-growing, requesting a room for a more reliable test. The area of AI has developed, and it does not intend to build and rely on human-like intelligence, it has been able to incorporate different behaviors to the machines to be exhibited in different environments.
Why AI is a part of new media
Artificial intelligence uses a combination of large volumes of data and high-speed processing of algorithms to learn from the characteristics of data (Khan 2). The following are some of the AI sub-disciplines that make it part of the New Media.
Machine learning uses algorithms and mathematical models that enable the computer to learn automatically without a need for programming. Machine learning is based on the idea that systems can learn from data, identifying patterns, and also making decisions with minimal human intervention. Artificial intelligence is part of the New Media in this network because the present interest is in the growing volumes and varieties of available data, computational processing that has become cheaper and more powerful.
A neural network uses neurons to process data received and changes its state depending on the data collected and produce outputs. The systems are developed by the inspiration of neuron functionality in the brain. They replicate the way humans learn. The tools o neural networks are used for finding patterns that are numerous and complex. This way, the programmers can retrieve and train the machine also to recognize the patterns. Artificial intelligence is the new wave of most business applications and commercial companies that use such technologies for their operations. The main aim is to solve complex problems like data analysis and weather prediction.
Deep learning, a sub-field machine learning, simulates the human brain by using neural networks to learn from the data. Deep learning has networks that are capable of learning without supervision from unstructured or unlabeled data. The evolution of deep learning has been such that the digital era has brought about an explosion of data in all forms and from all regions of the world. Unstructured data is usually vast, and it could take decades for humans to comprehend it also extract relevant information. Companies have realized the incredible potential that results from unraveling the wealth of such information hence increasingly adapt to the artificial intelligence systems for automated support.
Cognitive computing is a field of AI that aims to achieve normal interaction between machines and humans. Cognitive computing involves the use of computerized models to simulate the process of human thought during complex solutions where there are uncertain or ambiguous answers. Systems of cognitive computing can synthesize data from information sources as they weigh context and conflict evidence to suggest the best possible solutions.
Computer vision uses deep learning and machine learning to identify videos and images. Computer vision trains computers to interpret and understand the visual world. The machines have the ability to accurately identify and also locate objects then reacting to what they see with the use of digital images from cameras.
Natural language processing (NLP) enables machines or computers to interact with humans, using natural language. It entails applying algorithms that are used to identify and also extract rules of natural language. It is such that the unstructured language data to be converted into a form that can be understood by computers. When there is the provision of text, the computer utilizes algorithms to extract the meaning of every sentence and collecting essential data.
Since the advent of Artificial Intelligence in the 1950s, AI has evolved over the past 50 years, bursting into the market (Small 19). Organizations globally have invested up to $30 billion in 2016, of which 90% of this Investment was in research and development, and 10% was in the procurement of equipment (Small 19). This Investment is mostly in the technology sector, with companies like Google, Baidu, Microsoft, and Facebook being some of the dominating investors. Researchers further predict that Investment in artificial technology in Artificial Intelligence will continue to increase as organizations aim to be at the forefront of innovation and have a competitive advantage.
Such that, organizations that implemented an enterprise architecture capability shall have the ability to adapt quickly to change and innovation opportunities. This improvement shall help them increase their profit and level of competence. The fundamental to the strategic planning of the IT function is crucial in 4th industrial technology since it allows the organization to keep its tracks record about changes.
The 4th Industrial Technology strives to improve self-controlled systems, intelligence, and communication as part of the New Media. Besides, it covers four fundamental principles, such as internet technology, holistic security, and safety, including knowledge protection and privacy, component as information carriers, internet technology, and cyber-physical system. The four conceptual approaches, when combined together, help the smart system as a kernel feature of the 4th industrial technology application.
Today, artificial intelligence allows robots with no human morals and experiences to make death and life choices without any supervision from human beings and which can affect the population of human beings. Artificial intelligence makes countries of high financial ranking have a strong army enabling them to compete to weaponize. Artificial Intelligence gives countries powers to control nations with lower economic status. In this way, powerful countries gain advantages of executing powers that may interfere with people's lives. These incidences are supported by history, as was the case of Hitler's Holocaust, where one person man-handled and destroyed entire humanity.
Artificial Intelligence causes surveillance leading to exponential depravity of rights of the public to private. The emergence of Enterprise Architect may assist in designing Artificial Intelligence systems to restrict creating human and human-related errors and to address the ethical dilemmas. For instance, autonomous robots can perform different tasks without human supervision. Artificial intelligent robots are capable of performing multiple tasks compared to human beings as the body gets tired and slows down during later stages in life. For this reason, many people fear that they may lose their jobs, become extinct, or supplanted. Research has it that by 2025 Artificial Intelligence shall replace 52% of professional roles such as accountant, lawyers, and doctors.
Artificial intelligence Research as Art
Artificial intelligence research is a form of art because of the invention and elaboration of new technologies and the cultural possibilities of art practice. There have been new branches of knowledge, industries, social contexts and technologies that have come up and these developments are affecting everything that is part of the general activities (Wilson 171). Artists tend to establish practices whereby they participate at the core of the activity instead of distant commentators or just consumers of the gadgets.
More artists are using artificial intelligence to make their work even better for the audience they wish to please. Artists have the idea of using the artificial intelligence systems to understand and also replicate the artworks created by humans (Wilson 186). The technique of neural style transfer is used by arts in replicating and recreating the pieces of art. Artists use deep neural networks to perform the transformation of image and use the same concept for paintings, music, photography, video and other forms of art.
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