Man Studying AI Online

Recently, we explained why AI is so important, and we discussed how to launch a career in artificial intelligence, and here we’re going to explore how AI actually works.

As part of this discussion, we’ll cover what artificial intelligence is, what fields or disciplines AI uses, what technologies are involved in AI operations, and how AI solutions are being applied in the modern economy.

After you’ve learned all about how AI really works, fill out our information request form to receive additional details about CSU Global’s 100% online Master’s Degree in Artificial Intelligence and Machine Learning, or if you’re ready to get started, submit your application today.

What Actually Is Artificial Intelligence?

Before we can explain how AI works, let’s first define what AI is:

Artificial Intelligence is a technology that allows machines and computer applications to mimic human intelligence, learning from experience via iterative processing and algorithmic training.

You can think of AI as being a form of intelligence that is used to solve problems, come up with solutions, answer questions, make predictions, or offer strategic suggestions.

Because AI can do all these things, it’s become incredibly important to modern businesses and other types of organizations.

What is AI Really Doing?

AI systems work by combining large sets of data with intelligent, iterative processing algorithms to learn from patterns and features in the data that they analyze.

Each time an AI system runs a round of data processing, it tests and measures its own performance and develops additional expertise.

Because AI never needs a break, it can run through hundreds, thousands, or even millions of tasks extremely quickly, learning a great deal in very little time, and becoming extremely capable at whatever it’s being trained to accomplish.

But the trick to understanding how AI truly works is understanding the idea that AI isn’t just a single computer program or application, but an entire discipline, or a science.

The goal of AI science is to build a computer system that is capable of modeling human behavior so that it can use human-like thinking processes to solve complex problems.

To accomplish this objective, AI systems utilize a whole series of techniques and processes, as well as a vast array of different technologies.

By looking at these techniques and technologies, we can begin to really understand what AI actually does, and thus, how it works, so let’s take a look at those next.

What Disciplines Make Up the Field of AI?

There are many different components to an AI system, which you can think of as sub-fields of the overarching science of artificial intelligence. 

Each of the following fields is commonly utilized by AI technology:

  • Machine Learning - A specific application of AI that lets computer systems, programs, or applications learn automatically and develop better results based on experience, all without being programmed to do so. Machine Learning allows AI to find patterns in data, uncover insights, and improve the results of whatever task the system has been set out to achieve.
  • Deep Learning - A specific type of machine learning that allows AI to learn and improve by processing data. Deep Learning uses artificial neural networks which mimic biological neural networks in the human brain to process information, find connections between the data, and come up with inferences, or results based on positive and negative reinforcement.
  • Neural Networks - A process that analyzes data sets over and over again to find associations and interpret meaning from undefined data. Neural Networks operate like networks of neurons in the human brain, allowing AI systems to take in large data sets, uncover patterns amongst the data, and answer questions about it.
  • Cognitive Computing - Another important component of AI systems designed to imitate the interactions between humans and machines, allowing computer models to mimic the way that a human brain works when performing a complex task, like analyzing text, speech, or images.
  • Natural Language Processing - A critical piece of the AI process since it allows computers to recognize, analyze, interpret, and truly understand human language, either written or spoken. Natural Language Processing is critical for any AI-driven system that interacts with humans in some way, either via text or spoken inputs.
  • Computer Vision - One of the prolific uses of AI technologies is the ability to review and interpret the content of an image via pattern recognition and deep learning. Computer Vision lets AI systems identify components of visual data, like the captchas you’ll find all over the web which learn by asking humans to help them identify cars, crosswalks, bicycles, mountains, etc.

What Technology Does AI Require?

AI isn’t new, but its widespread application and utility have skyrocketed in recent years thanks to considerable improvements in technology.

In fact, the explosive growth of AI’s scale and value is closely related to recent technological improvements, including:

  • Larger, More Accessible Data Sets - AI thrives on data, and has grown in importance alongside the rapid increase of data, along with better access to data. Without developments like “The Internet of Things”, which produces a huge amount of data from connected devices, AI would have far fewer potential applications.
  • Graphical Processing Units - GPUs are one of the key enablers of AI’s rising value, as they are critical to providing AI systems with the power to perform millions of calculations needed for interactive processing. GPUs provide the computing power needed for AI to rapidly process and interpret big data.
  • Intelligent Data Processing - New and more advanced algorithms allow AI systems to analyze data faster and at multiple levels simultaneously, helping those systems analyze data sets far faster so they can better and more quickly understand complex systems and predict rare events.
  • Application Programming Interfaces - APIs allow AI functions to be added to traditional computer programs and software applications, essentially making those systems and programs smarter by enhancing their ability to identify and understand patterns in data.

How is AI Being Applied?

To fully get how AI works, it’s also important to understand where and how it’s actually being applied.

Fortunately, there are many examples of AI’s use in the modern economy, including: 

  • Retail - AI systems are being consulted to design more effective store layouts, handle stock management, and provide shopping suggestions, like via Amazon’s “You May Also Like” recommendations. 
  • Healthcare - AI technology has been trained to provide personalized medicine, including giving reminders about when patients need to take their medicine and suggestions for specific exercises they should perform to improve their recovery from injuries.
  • Manufacturing - AI solutions help forecast load and demand for factories, improving their efficiency, and allow factory managers to make better decisions about ordering materials, completion timetables, and other logistics issues.
  • Life Sciences - AI intelligence is actively applied to review complex data sets that are useful in testing new medicines, helping life science organizations get effective medicines to market faster.
  • Finance - AI tools are being leveraged to detect and prevent fraudulent financial transactions, provide more accurate assessments than traditional credit scores can, and automate all sorts of data-related tasks that were handled manually.

Why Should You Consider Studying AI?

AI technologies are being developed and applied to virtually every industry, helping improve results, automate processes, and enhance organizational performance.

The AI industry itself is growing rapidly, with the International Data Corporation (IDC) reporting that the AI market, “including software, hardware, and services, is forecast to grow 16.4% year over year in 2021 to $327.5 billion.”

Top jobs in the field also tend to come with great salaries, with Glassdoor reporting that the average salary for AI engineers is $127,303 and $146,521 for AI development professionals.

If you’re interested in pushing the boundaries of computer technology and you want to launch a career in a field that’s growing, and pays well, then AI may be the perfect opportunity. 

Why Should You Study AI With CSU Global?

CSU Global’s online Master’s Degree program in AI and Machine Learning offers an excellent opportunity to develop your skills, knowledge, and abilities in this competitive field.

Our AI and machine learning program is regionally accredited by the Higher Learning Commission and widely respected by industry professionals, while CSU Global itself is a recognized industry leader in online education, having recently earned several important awards, including:

  • A #10 ranking for Best Online Colleges for ROI from OnlineU.
  • A #1 ranking for Best Online Colleges & Schools in Colorado from Best Accredited Colleges.
  • A #1 ranking for Best Online Colleges in Colorado from Best Colleges.

We also offer competitive tuition rates and a Tuition Guarantee to ensure that your tuition rate won’t increase from enrollment through graduation.

To get additional details about our fully accredited, 100% online Master’s in AI and Machine Learning program, please give us a call at 800-462-7845, or fill out our Information Request Form.

Ready to get started today? Apply now!