Relation between Artificial Intelligence and Machine Learning

Relation between Artificial Intelligence and Machine Learning

Nowadays Artificial Intelligence and Machine Learning have created a lot of buzz around and are often seen to be used interchangeably. They are quite not the same thing but the perception that they are can lead to confusion sometimes. In short we can say that Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider smart and Machine Learning is being used as a current application of AI-based around the idea that we should really just be able to give machines access to data and let them learn for themselves.

Machine learning is a subfield of artificial intelligence. Its goal is to enable computers to learn on their own. A machine’s learning algorithm enables it to identify patterns in observed data, build models that explain the world, and predict things without having explicit pre-programmed rules and models. It allows software applications to become more accurate in predicting outcomes without being explicitly programmed. The basic premise of machine learning is to build algorithms that can receive input data and use statistical analysis to predict an output value within an acceptable range. Machine Learning is used in complex systems where human fail to perform in a small time interval. For the massive quantity of data to store and delivering faster results with high accuracy machine learning is the best platform. With many advances in machine learning methodologies development have been done. It is observed from the various surveys that Artificial Intelligence is the future of Growth.  There are some Artificial Intelligence software companies available which provide the number of services in this field. Machine learning is a part of Artificial Intelligence.

Artificial Intelligence aims to create expert systems and implement human knowledge in machines. AI is accomplished by studying how human brain thinks and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems. Machines are programmed for some characteristics such as reasoning, knowledge, problem solving, planning, learning and manipulating abilities. Artificial Intelligence outcomes are used for developing intelligent devices and system. Some examples of artificial intelligence are speech recognition, smart cars, fraud detection etc. Today it has become more popular and the credit goes to increasing volumes of data, advanced Machine Learning Algorithms and improvement in computing storage and power. We all are aware of the fact that in the near future the human-like robots will take over the world and which will prove to be a benefit for various industries.    Machine Learning is considered as the primary driver behind AI development. Artificial Intelligence makes machine smarter whereas Machine Learning makes them intelligent.  Machine Learning algorithms can practice more information and find out more patterns than humans can do. Machine learning can recognize risk factors in a better way for sickness in a large population area.  Machine learning services are wooing more customers due to its smart learning techniques. Self-learning algorithms are now routinely embedded in mobile and online services. Researchers are getting massive gains in processing power and data streaming from digital devices and connected sensors to improve AI performance.

Conclusion: Here in this article we have discussed what Machine learning is and what Artificial Intelligence is and what is the basic difference between the two and how are they interlinked and what are the various applications. AI techniques are using Machine Learning strategies and it’s becoming popular. Still, research is continued in this field to attain final objectives. For decision making, artificial intelligence is adopted. Further to enhance its performance machine learning is applied. Nowadays artificial intelligence is everywhere, mostly in every application which we are using. It has become a strong part of our life. These technologies have moved intelligence from computational programs to real models. Still research work is being done on it to attain human-level intelligence.

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