The 21st century accounts for a tremendous advancement in the field of information and technology. Most importantly, AI (Artificial Intelligence). Technologists would know what compliments AI is machine learning. Let’s dig deep and understand them individually.
About
AI
Also known as machine intelligence, Artificial intelligence is the learning ability of machines. It includes machines to understand, interpret, predict, adapt and come to a self-driven conclusion. Other intelligent features of AI include:
- Knowledge
- Problem-solving
- Learning
- Predicting
- Reasoning
Machine Learning
On the other hand, we have machine learning. An integral part of artificial technology, machine learning supports computerized systems to understand, interpret and derive independently. It follows a simple cyclic pattern:
Training data- Machine Learning Algorithm– Model Input- New Input Data- Machine Learning Algorithm- Predict- Machine Learning Algorithm.
Features
AI
Artificial intelligence is subsequently divided into two features namely, Machine Learning and Deep Learning. Where on one hand machine learning accounts for more statistical data analysis, problem-solving and perception.
On the other hand, deep learning digs deeper allowing machines to create a network for analysis and decision making.
Machine Learning
Features of machine learning are similar to that of AI. Such as,
- Character recognition
- Speech recognition
- Pattern recognition
- Spam deduction.
Are, to say the least.
Example
AI (Artificial Intelligence)
There are several examples in our day to day life of Artificial intelligence that we can find. From smartphone to televisions and smart cars, every fragment of technology is associated with artificial intelligence in a way or the other.
Applications like Gmail, Netflix, Apple Music and more use artificial intelligence to track your preferences.
Machine Learning
Samples of machine learning are found in artificial learning itself. If for example, Netflix uses artificial intelligence to set recommendations for you.
Machine learning sets a pattern using models, training data, algorithms to create a network that results in an artificially formed intelligence. If you want to learn more see how Machine learning works in detail.
Differences
Artificial intelligence and Machine learning differ in their functionalities. Where artificial intelligence is the ultimate result of a combination of permutation and integration, Machine learning is a part of it. Machine learning paves a path for artificial intelligence to resuscitate.
Similarities
While there is the difference in how the two are perceived, they are similar in various senses. Both AI and ML are computerised programming whose ultimate goal is to develop a more profound technological system.
They are developed by humans for the convenience of humans. Both depend on the integration of neural networks, just like a human nervous system. The neurons depict complicated data, detect trends and learn using examples.
Conclusion
At the end of the day be it Artificial Intelligence, Machine Learning or Deep Learning their wider picture is to solve human problems. In order to completely understand artificial intelligence, you need to first get the concept of machine learning. If AI is the body, machine learning is the brains.
It is crucial to note that a lot of tests go into developing an AI. Its implementation in robotics is the future of technology.
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