Artificial Intelligence Write for Us
Artificial intelligence (AI) is a framework for simulating human intelligence processes by creating and applying algorithms embedded. in a dynamic computing environment Simply put, AI aims to make computers think and act like humans.
Achieving this goal requires three key components:
- Computing
- Data and Data Management
- Advanced AI Algorithms (code)
The more human the desired outcome needs to be, the more data and computing power will be required.
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How did AI Start?
Since at least the first century BCE, persons have been interested in the likelihood of creating machines that mimic the human brain. The term “artificial intelligence” was invented in 1955 by John McCarthy. In 1956, McCarthy and other scientists organised a meeting called the Dartmouth Summer Research Project on Artificial Intelligence. This initiative led to machine learning, deep learning, predictive analytics, and prescriptive analytics. It also gave birth to a new field of study: data science.
Why is Artificial Intelligence Necessary?
Today, the quantity of data generated by humans and machines far exceeds human ability to digest, interpret, and make complex decisions. Artificial intelligence underlies all machine learning and is the future of complex decision-making. For example, most humans can learn not to lose at tic-tac-toe (three-by-three), even though there are 255,168 sole moves, 46,080 of which end in a draw. Fewer people could be considered champions at checkers, with over 500 x 10¹⁻ (500 trillion) different potential moves. Computers are incredibly efficient at calculating these combinations and permutations to make the best decision. AI (and its logical extension into mechanism learning) and deep learning are the important future of business decision-making.
AI Applications
Examples of AI use cases can be seen in everyday situations such as fraud detection in financial services, retail purchase predictions, and online customer interactions. Below are some examples:
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- Learning
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