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What is AI?

Carlos F Corvera | 21 February, 2022 | Modern Workplace

Artificial Intelligence, or AI, can seem daunting when it comes to your business. But it’s actually quite simple.

The goal of AI is to create systems that function intelligently and independently to solve real-world problems.

The way computers use AI is pretty similar to the way we humans process the world around us. In fact, AI is achieved by analysing human behaviour and using the outcome to develop intelligent systems.

HumansAI
Communicate by talking & listeningSpeech recognition
Read & writeNatural language processing
EyesightSymbolic learning (computer vision)
Recognising & processing surroundingsImage processing
MovementRobotics
Pattern recognition, e.g. spotting groups of similar objectsPattern recognition (but on a far greater scale)
Use a network of neurons (brain) to learn thingsMachine learning through an artificial neural network
Scan images through eyes, e.g. from left to rightMachine learning through a convolutional neural network (object recognition)
Remember the pastMachine learning through a recurrent neural network

So how does AI do all that?

AI works in two ways:

Symbolic AI

Applications process strings of characters (symbols) and a hierarchical representation of knowledge to reflect real-world problems.

Symbols can be used to define things (for example, human, cat, dog). They can describe actions (running, walking, sleeping) and they describe hierarchies (a human is made of a skeleton, muscles, nervous system etc).

On a computer, symbols can be arranged in structures such as lists, hierarchies or networks. The structures define how the symbols relate to each other. 

Data-based AI (Machine Learning)

Humans have a brain, which is a neural network. Computers also have a sort of brain, an artificial neural network, which can process huge quantities of data.

Artifical-Neural-network

Machine learning is used to classify data and make predictions with that data.

If you have data on your sales revenue and marketing costs you can plot out that data to look for patterns. A computer can also learn this pattern, then make predictions based on what it learned.

Humans use a few different methods to predict patterns, but computers use thousands of methods. This means they can make predictions we’d never be able to come up with.

What are the different types of machine learning?

Supervised learning: training an algorithm with data that also contains the answer.

For example, you can train a computer to greet your family members by their names, but first you’ll need to tell the computer who each family member is and what their name is.

Unsupervised learning: training an algorithm with data that you want the computer to use to identify patterns.

For example, you can enter data into a computer about your sales opportunities and their status, and ask the computer to come up with patterns in that data by itself.

Reinforcement learning: give an algorithm a goal and expect the computer to achieve that goal through trial and error.

For example, you can program a robot arm to try to pick up an egg without breaking it until it succeeds.

Ready to find out how AI can benefit your business?

We love to help, have a chat with us today and find out how we can help your business.

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