Artificial Intelligence (AI) and Machine Learning (ML)
The Understanding of Artificial Intelligence and Machine Learning
Artificial Intelligence (AI) is the umbrella term for human-made intelligence to mimic human cognitive functions. Machine Learning (ML) is the subset application of Artificial Intelligence. Artificial Intelligence is the technology that simulates human intelligence to solve problems autonomously.
Definitions
Artificial Intelligence (AI) is the umbrella term for human-made intelligence to mimic human cognitive functions. Machine Learning (ML) is the subset application of Artificial Intelligence.
John McCarthy
The term “autonomously” means that AI can do things without any human intervention. Such as taking actions on its own or making decisions. Machine Learning analyzes the data and then explores all the possibilities of the provided data using statistical tools.
Before, we humans used to make rules for everything while teaching something to others. But not anymore, now instead of making all the rules by humans for the machine, we let machines make their own rules by themselves. We do that by giving the machine lots and lots of data which is called “Big Data”. The machine makes its own rules by utilizing different kinds of Machine Learning algorithms and techniques according to its requirements and needs. This enables the algorithms and techniques to continue learning and keep improving on their own.
Explicit knowledge is something that can be written down on a piece of paper and can be learned through instructions. Some examples of Explicit knowledge are; this is how you operate a camera, this is how you build a house, this is how you solve a puzzle, etc.
Tacit knowledge is something that cannot be written down on a piece of paper and can only be learned through experience. Some examples of Tacit knowledge are like; this is how you love, this is how you cycle, this is how to speak English, etc.
Since we cannot provide Tacit knowledge to a machine we need a way for the machine to learn these kinds of knowledge by itself. Machine Learning is only good at learning one particular thing at a time and if that same algorithm is used on anything else besides that particular thing, then Artificial Intelligence will fail!
When Artificial Intelligence tries to recognize an alphabet or an object, the Machine Learning algorithm takes all the information and data about that particular alphabet or that particular object and then creates its own system.
The system then can identify that particular alphabet or that particular object by calculating how high is the probability or certainty of the given data being from that particular alphabet or that particular object. Finally, Artificial Intelligence displays that probability or certainty information on the screen in a human-understandable readable format.
Basically, this is all about pattern recognition and how good the algorithms and techniques are at recognizing these patterns and then conveying that information in simplicity. However, General Artificial Intelligence is the idea of exhibiting intelligence including abstract thinking, showing creativity, making strategy, etc.
Hence Artificial Intelligence is the grand vision of intelligent machines. Machine Learning on the other hand is the models, processes, and supporting technology. Artificial Intelligence is the things at the frontend that human beings can see and absorb, but Machine Learning is the things at the backend that human beings cannot see and absorb.
Article by: Mr. Sajit Shekhar | Content Editor: Salina Shree
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