Brief Introduction to Artificial Intelligence

Artificial Intelligence is the study and production of computer systems which can perceive, act, and reason. The main goal of AI is to produce smart machines. The intellect should be demonstrated by believing, making decisions, and solving problems. AI is an interdisciplinary field which demands knowledge in computer science, linguistics, psychology, biology, and philosophy. AI might also be defined as the field of computer science that addresses the ways wherein computers could be made to do cognitive functions ascribed to humans. However, this definition does not say what works are done, to what level they're done, or the way theses functions are performed. 

AI draws heavily on subsequent domains of study: Computer Sciences, Cognitive Science, Engineering, Ethics, Linguistics, Logic, Math, Natural Sciences, Philosophy, Physiology, Psychology, Statistics, and more.

Powerful Artificial Intelligence - Deals with production of real-intelligence unnaturally. Strong AI considers that machines could be made sentient or self aware. The two main types of strong AI: Human such as AI, wherein the computer program considers various motives to the degree of human being. Nonhuman like AI, wherein the computer software develops a nonhuman way of reasoning and thinking. Strong AI is only effective with the implementation of machine learning supporting it.

Weak Artificial Intelligence - Weak AI doesn't believe that producing human level intelligence in machines is possible, but AI techniques could be developed to solve many authentic life problems. Rather, it is the research of mental models implemented on servers.

AI and Nature - Today AI techniques developed with the inspiration from nature are extremely popular. A brand new area of research what's known as Nature Inspired Computing is emerging. Biological inspired AI approaches like neural networks and genetic algorithms are striving to produce strong AI methods leveraging machine learning models.

Challenges - It's true that AI alone doesn't recognize and remember different objects, adapt to new circumstances, understand and generate human languages without the assistance of machine learning. Without implementing sophisticated algorithms that adapt to new stimuli to learn from previous assumptions, AI is stuck in a binary function.

AI systems alone without machine learning backing do not produce abilities beyond that of a 3 year old. They do not have the capability to understand how the human brain works, how we learn new things, or how we learn languages and replicate them properly.

AI techniques are utilized to solve many real life problems; however, the need for a deeper implementation of machine learning and algorithmic training is necessary to truly unlock the full potential of AI. There is rapid, ongoing research surrounding AI and machine learning with the promise of a rewarding, intellectual career should it be of interest to you. If this is of interest, I implore you to dive in and find out how your skills can be used to progress the expansion of AI technologies.

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Author: Bryce Jurss