What is Artificial Intelligence
Artificial Intelligence (AI) is the technology building smart machines able to perform tasks that generally need Human Intelligence.
There are two broad types of Artificial Intelligence:
- Narrow AI
- Broad AI
Narrow AI
Narrow AI is the type of AI which performs a single take. It’s being able to carry out specific tasks that intelligent systems have been taught without being sophistically programmed, this is why it’s called Narrow AI. To give you a better understanding, it’s Siri for Apple users. Examples of this are self-driving cars and voice recognition to help radiologists pick up tumors.
Narrow AI is based on Machine Learning and Deep Learning
Machine Learning
Machine learning consumes data and uses statistics to better learn the data, in turn improving the ability to solve the task. Machine learning is made up of both supervised and unsupervised learning. Supervised learning learns on a labeled dataset, allowing you to produce outputs based on previous data. In contrast, Unsupervised learning uses unlabeled data to learn on and discover unknown patterns in data.
Deep Learning
Deep learning, also known as deep neural learning, is a type of machine learning technique that tries to imitate the human brain by inputting data through a biological-inspired neural network that contains a number of hidden layers. Through the hidden layers, the data is processed making connections and creating patterns.
General AI
General AI has a bit more complexity to it and tries to mirror human intellect using its ability to learn and apply the knowledge learnt to solve problems. We are now going through the process of transitioning from Narrow AI to General AI, for example, natural language processing. In order to achieve this, computer hardware needs to advance in computational power to perform at a better rate.
Examples of AI Applications
Below are some examples of AI applications to give you a better understanding of how it has been implemented:
- Speech recognition: This is the process of enabling a computer to recognize spoken words and have the ability to respond, for example; Siri.
- Natural Language Processing: This enables software to understand, interpret and generate the human language, for example; language translation and email filtering.
- Image recognition: This process can classify text, people, and objects as well as moving images. Examples of this are; fingerprint ID systems, self-driving cars, and face recognition.
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