Artificial Intelligence: Bridging the Gap to Human-Level Intelligence Essay

 

 

Numerous functions characterize human intelligence and some of them are implemented in artificial intelligence systems, but the main difference between human and artificial intelligence is the ability to synthesize new knowledge and identify unknown patterns. Most artificial intelligence systems from the very beginning relied not on mathematical apparatus but on logical-linguistic systems, which previous computing systems were unable to do (Anderson et al., 2018). Currently, hybrid intelligent systems also include various mathematical methods of analysis. Nevertheless, a knowledge base containing formalized knowledge for a specific field is mandatory for intelligent systems, for which different knowledge representation languages are used.

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One of the leading artificial intelligence technologies in modern times is a neural network. There are parameters in the neural network function that are trained based on the received data, and the more data, the better it learns. The neural network borrows the principle of operation from neurophysiology, and in composition, it resembles the human brain (Laudon & Laudon, 2019). Its algorithm is built so that artificial intelligence learns independently when solving many similar tasks, which it takes from a vast array of data. There are a lot of directions in the development of artificial intelligence now: robotics, search, machine learning, knowledge representation, planning, language processing, and multi-agent systems (Anderson et al., 2018). Scientists are creating something that previously seemed accessible only to human intelligence.

The ultimate goal of artificial intelligence is to create computer programs that can solve problems and achieve goals in the same way as a human. Human-level intelligence can be achieved by writing many programs and collecting extensive knowledge bases about facts in languages used today to express knowledge (Laudon & Laudon, 2019). For artificial intelligence, it is essential that when solving problems, algorithms are as effective as the human mind.

References

Anderson, J., Rainie, L., & Luchsinger, A. (2018). Artificial intelligence and the future of humans. Pew Research Center. Web.

Laudon, K. C., & Laudon J. P. (2019). Management Information Systems: Managing the digital firm (16th ed.). Pearson

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