Difference Between Machine Learning and Artificial Intelligence
AI is a non-natural or human made intelligence which has the ability to think. AI can be categorized into two, mainly General and Narrow. General AI would have almost all the characteristics of human intelligence. Narrow AI consists of certain features of human intelligence. A machine capable of recognizing only the sounds around it can be an example for narrow AI.
- AI is known as the study of training computers so that they can do whatever the humans do very well
- AI aims at increasing the chance of success rather than accuracy
- It works as a smart computer program
- It also aims at stimulating natural intelligence to solve complex issues
- Decision making is done using AI
- AI goes to find the optimal solution
- AI leads to wisdom or intelligence
Internet of Things (IoT) needs some element of AI for working. IoT is a collection of big data which can help humans achieve what they intend to have.
AI and IoT are inextricably tangled. It’s like how human brain and body is related. IoT collects the data essential and AI analyses it and brings out meaning out of the collected data ad decides how to take action.
A machine learns on its own without explicit programming when it comes to ML. AI can provide the system ability to automatically learn and improve from experience.
- ML is defined as the acquisition of skill or knowledge
- It aims at accuracy and is not concerned about success rates
- The machine takes data and learns from it in this case
- It learns from data to maximize the performance of the machine
- It allows system to learn new things from the acquired data
- ML creates self learning algorithms
- ML goes for solution, not considering whether its optimal or not
- ML leads to knowledge
Deep learning is one of the many approaches to machine learning. Deep learning was inspired by the structure of the brain, namely the interconnecting of many neurons. Artificial Neural Networks (ANN) are algorithms which mimic the brain structure. In ANN, there are layers which are connected to other neurons. It is this layer that gives the name deep learning, where depth is created using multiple layers rather than a single layer.
Machine learning and Deep learning have benefitted AI in a lot of ways. All this requires massive amount of data and that data is collected by IoT. Thus IoT makes better AI. AI can also be used to identify when machines need servicing and maintenance to work efficiently and thereby saving millions when it comes to a huge company or an organization.
Thinking from a consumers perspective, rather than clicking, typing and searching, if we ask for answers or solutions and get it, that can make us believe when compared to checking all the search results and finding out the apt one for us.
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