Humans have dreamt about creating intelligent machines since ancient times – but only made the first attempts to actually do this in the early 50s. Now, in 2021, we already have a number of tools at our disposal to turn those dreams into reality.
Having said that, the topic is still quite complex. Which is exactly why we’re here to answer the question: how does Artificial Intelligence work?
What is Artificial Intelligence?
Artificial Intelligence (AI) is an interdisciplinary science focused on building machines able to complete tasks that typically require human intelligence.
Machines equipped with this technology are capable of learning from experience, processing data, and recognizing patterns, or even create completely new data as in the case of Generative AI technology.
Crucially, AI is able to perform those tasks without being explicitly instructed – its algorithms process data similarly to natural intelligence. Thus, AI can make reasonable decisions based on solid data, as well as predict their far-reaching consequences.
- If you’d like to learn more about AI in business, check out our Artificial Intelligence Guide!
What are the types of Artificial Intelligence?
Before we explain how Artificial Intelligence works, we need to underline the fact that there are different types of AI exploring various scopes of tasks and mechanisms. The technology itself is split into three broad categories:
- Narrow AI, also called “Weak AI”.
- Artificial General Intelligence (AGI), also called “General AI”.
- Artificial Super Intelligence (ASI), also called “Strong AI”.
Narrow Artificial Intelligence
This is the most recognised type of AI, as it is widely used in many different fields. Narrow Artificial Intelligence (also called weak AI) is usually focused on performing one particular task and is meant to only imitate human intelligence. It typically operates under a number of limitations, requires prior supervision and input delivery.
Though you may not have heard about the term before, there’s a very high chance you’ve used a Narrow AI-powered tool at some point. Some examples of Narrow AI’s use include Google search algorithms, image recognition software or personal assistants like Alexa or Siri.
Artificial General Intelligence
AGI is supposed to be more complex than Narrow AI. The goal here is for the machine to perform tasks just as a human would, and become able to solve problems on its own. Thus, General AI should overcome the limitations of Narrow AI. Not only could it be used for a large variety of tasks instead of just one, but it is assumed that just as a human, it should be able to apply what it’s learned from one field to another.
Contrary to some sensational headlines that you may have seen over the years, Artificial General Intelligence is still yet to be developed, and some even argue that it’s simply not possible. We’ll simply have to wait and see what the future holds.
Artificial Super Intelligence
While many believe that we may be able to create AGI at some point in the future, Artificial Super Intelligence is considered a work of fiction for the most part.
ASI is supposed to be the most advanced type of AI, which not only imitates human intelligence but is also able to perform self-awareness. It equips machines with emotions, beliefs, and desires typical for humans. Crucially, ASI not only catches up to but also surpasses human abilities.
Now that we know the main types of AI, let’s get to the gist of it!
How does AI work?
Artificial Intelligence is based on various disciplines that we have been developing for ages. Modern AI is inspired and supported by philosophy, economics, medicine, mathematics, psychology, neuroscience etc.
Explaining how Artificial Intelligence development services works is fairly simple: it uses large sets of information and data in order to make the machine learn and perform tasks based on that knowledge.
Building a set of algorithms that can ensure AI’s performance is a complex process of reverse-engineering human capabilities, behaviours, and traits.
But to fully grasp how it’s all done, it’s essential to understand that Artificial Intelligence is based on a few subdomains that can be applied to a number of projects, and its careful combination results in intelligently behaving machines. Having said that, let us go through the most important AI subfields and see what they’re made of.
Machine Learning
Machine Learning solutions are by far the most commonly used AI method. The scope of ML is teaching a machine to make decisions based on past experience, structured, and semi-structured input. It deals with analysing data, recognizing patterns, and coming up with a reasonable output. It is widely used wherever there is a need to automate and optimise tasks normally performed by humans.
Deep Learning
Often confused with ML, Deep Learning is in fact ML’s specific facet focused on teaching the machine to process data through a special kind of very complex algorithms – neural networks. It is a go-to technique when we want to build intelligent applications dealing with images, videos, text, and sound. With Deep Learning, you’re able to discover hidden data patterns that you wouldn’t find otherwise.
Curious? Check out our detailed Deep Learning vs Machine Learning comparison and discover the main differences between them!
Natural Language Processing
NLP is a tool is focused on exploring language: reading, interpreting, and producing text and speech. NLP mechanisms are able not only to understand but also to respond to the user in a matter that’s similar to human conversation. With NLP, the machine is able to identify the meaning of words, and even understand the context behind them – as it is widely used in voice assistants, including Google Assistant and Siri.
Computer Vision
This part of AI technology is dedicated to studying visual objects. Combined with Deep Learning techniques, Computer Vision software is capable of interpreting the content of images and videos. With computer vision, we can, for example, authenticate the person who wants to use our services, classify objects found in pictures and search content by images.
Artificial Neural Network
The idea of a neural network is loosely based on how a human brain is built. Neural networks are algorithms built from sequenced blocks, called layers. They are made of a complex set of algorithms making it possible to process data in many ways, depending on the application. This allows neural networks to handle data as complex as videos, images, and text.
Cognitive Computing
Cognitive Computing is the newest AI mechanism trying to mimic the human brain. It analyses various content, including text, speech, and visual materials – the same way that humans do. The aim is for the machine to become able to solve complex problems and come up with the most reasonable answers to them. It can be a very useful tool for assisting humans in their work and coming up with solutions that we’d miss otherwise.
How to choose the right Artificial Intelligence solutions
To successfully decide what kind of AI technology is the best fit for your project, it’s crucial to carefully analyze your business needs, the desired features of the product, and the technological assets at your disposal.
Want to learn more about AI solutions, and see which ones are best suited for your business needs?
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