In the words John McCarthy, the father of artificial intelligence, “AI is the science and engineering of making intelligent machines, especially intelligent computer programs”. Therefore, artificial intelligence emphasises on the creation of an intelligence within a computer/robot or software that enable the functioning of diverse abilities (such as reasoning, problem solving, learning, thinking and so on) without human intervention. AI focuses on machine to machine interaction at advanced levels of performance. Artificial intelligence primarily has a variety of branches that devout in specialization of a certain ability or performance. Some of the branches include:
1. Machine learning
2. Knowledge engineering
3. Natural language processing
4. Real-time emotion analytics
5. Pattern recognition (vision)
6. Robotics
This article addresses Artificial Intelligence with specific attention to Machine Learning. Having now defined artificial intelligence let us explore more on machine learning.
Machine learning is one of the most important qualities of artificial intelligence that enables successful M2M communication and deep learning. It is this feature that provides ample intelligent characteristics to computers, remotes that control robots and even software programs. Machine learning is not new to AI, but it is a science that has gained new momentum. The new momentum refers to the building of algorithms that collect data and implement statistical analysis which enables the generation of a predictive data output and simultaneously updates itself with new available data from time to time. Therefore, machine learning is the essential fuel to reliable and accountable functioning of artificial intelligence. Together, they help achieve automation solution in various realms.
Example:
In today’s world, majority of people across the globe have social media accounts that are handled on a day to day basis. Have you ever wondered how you have a list of recommendations suggested for you? If not, then here you go, it’s the concept of machine learning that works behind recommendations engine. Data regarding your search list is collected, using statistical analytics predictive output is displayed as recommendations.
Use case:
A recent survey by IBM with auto executives suggests that 74% of them expected to witness smart cars by 2025. Such cars would not only integrate with Internet of Things but also learn of the owner and its environments that will enable it to perform internal settings and control (temperature, audio, seat position, auto pedestrian detection that stops car and so on) get automated.
To conclude, a simple analogy to what is AI and Machine Learning would be; how the brain is responsible for proper functioning of human beings, similarly AI and machine learning help a computer, robot or software application to work intelligently along with automation.
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