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Название: Robotics: What Beginners Need to Know about Robotic Process Automation, Mobile Robots, Artificial Intelligence, Machine Learning, Autonomous Vehicles, Speech Recognition, Drones, and Our Future
Автор: Neil Wilkins
Издательство: Amazon Digital Services LLC
Год: 2019
Страниц: 116
Язык: английский
Формат: epub, pdf (conv)
Размер: 10.6 MB

Artificial intelligence, otherwise known as AI, is often referred to as machine intelligence and it is the intelligence that is commonly shown in machines as opposed to the natural intelligence that is usually seen in humans and various other mammals. When it comes to computer science, artificial intelligence research is going to be listed as a study of intelligence that is shown by devices that can perceive the environment around it in order to take actions that can maximize its chances of being successful in reaching its goals. Informally, the word artificial intelligence will usually be linked to a machine that can copy a human’s cognitive function problem-solving or learning.

Artificial intelligence was classified into three different classes by Kaplan and Haenlein, which they borrowed from the management literature – humanized artificial intelligence, human-inspired, and analytical. Analytical artificial intelligence is going to only have characteristics that are consistent with cognitive as well as emotional intelligence when it comes to understanding, as well as recognizing, cognitive elements and human emotions that are factored into the decisions they make. Humanized AI shows characteristics of every competency (emotional, cognitive, emotional, and social intelligence) as well as being self-aware and self-conscious enough to have interaction with others. Human-inspired artificial intelligence must all have human-like appearance besides its perceptive, social, and cognitive abilities. They must be able to clearly communicate with the use of natural language.

Many AI algorithms can learn from the data that they gather, which can help them enhance themselves by learning new heuristics or help them write other algorithms. There are some learners that you will see described below that include the nearest neighbor, decision trees, and Bayesian networks that could potentially be helpful – should it be given an infinite amount of memory, time, and data to approximate any function, which includes whatever combination of mathematical functions that would best describe the whole world.

Robotics is considered an exhaustive branch of science and engineering. Robotics encompasses different fields of engineering such as electronics, information, mechanical, computer science, and so much more! It is typically related to the use of robots, how they are invented, how they operate, and the computer system that is used to control the robot. It also includes feedback from sensors as well as the processing of information that the robot has to use.

‘Machine learning’ refers to the subfield found in PC (Personal Computer) science where PCs are given the tools needed to learn without being programmed by a person. Machine learning tends to overlap with PC statistics where predictions are made through a PC that has strong ties to optimize mathematical equations. This also makes it to where theories, methods, and applications dominate the field. Data mining, which uses data analysis, is often confused with machine learning. Unsupervised learning is what you also call data analysis. Even if it is unsupervised, machine learning should also learn to create a baseline for its behavior before finding meaningful anomalies.

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Автор: Ingvar16 15-10-2019, 18:37 | Напечатать |
 
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