The Machine Learning and Artificial intelligence the difference

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“A very general mental capability that, among other things, involves the ability to reason, plan, solve problems, think abstractly, comprehend complex ideas, learn quickly and learn from experience. It is not merely book learning, a narrow academic skill, or test-taking smarts. Rather, it reflects a broader
and deeper capability for comprehending our surroundings — ‘catching on’, ‘making sense’ of things, or ‘figuring out’ what to do” (Gottfredson, 1997)”

AI is not the new term but today its very hot every one in finance industry want to discuss its roles, rationales and human capabilities the essentials and exceptions to emulate human cognitive power, the expectation to supersede human intelligence benchmarks becomes the objectives among data scientists, business manager and C level executives The world economic forum presented report of the major characteristics of AI and its suites of categories

Pattern detection
To find out the specific behavior or sort out the regularities in data.

Foresight of learned patterns
To analyze the uncertainty in patterns.

By applying specific rules on data and optimize the outcome.

By applying the rules on data sets and extract the optimum decision

By applying rules and communicate humans through digital medium

Machine Learning
The concepts of AI and machine learning significantly overlapping with each other The term machine learning derived from the framework of learning on the neuroscience, statistic, transaction history and the mathematics the term machine learning coined by Mendel and McLaren (1970).The term “machine learning” related to changes in system against interaction with environment. A model interacts with its environment and changes its regularities may transform the business decisions and this process is repetitive in nature and to conclude machine learning is the process that find approximate solutions to the problems.

The difference

The machine learning depends on the involvement of the model with environment, the changes in model reflecting the changes in environment (Note: Environment is the business boundaries).The term AI is the name of a model which produce some changes in the environments after learning from previous instances.


Cloud technology and big data, Application Programming Interfaces (APIs), open-source algorithms and the Internet of Things (IoT) are often applied in tandem with AI (Duin and Bakhshi, 2018).

New Physics of Financial Services, affirmed that cloud computing provides the data storage and the processing power necessary to train new AI models, making cloud infrastructure critical in implementing AI solutions (McWaters et al., 2018).

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