Unraveling AI: Breaking Down Its Layers from Machine Learning to General Intelligence

by | Jun 15, 2024 | Artificial intelligence (AI)

Before we dive into some use cases, it’s important to lay out a few basic terms that define the technology we’re discussing:

  • Artificial Intelligence (AI): Like a Swiss Army knife, AI encompasses a range of tools and techniques that enable computers to simulate aspects of human cognition.
  • Machine Learning (ML): Instead of programming a computer every step of the way, ML enables it to learn patterns from data and make decisions with minimal human intervention.
  • Deep Learning (DL): DL is a subset of machine learning simulating the complex decision-making power of the human brain. By interpreting and processing data in layers, DL enables machines to recognize speech, identify images, or pilot autonomous vehicles.
  • Artificial General Intelligence (AGI): As opposed to the specialization offered by AI, ML, and DL, general AI refers to machine intelligence that can understand and learn in the same way as human beings can.

Real-World Applications

At this point, almost everyone has interacted with an AI-based technology at some point in their life. Whether it’s an online store giving you personalized recommendations or the last time you interacted with customer support, AI is everywhere and it’s not going away anytime soon. Here are a few real-world applications already putting AI to use.

AI Fast Food Drive-Thru

It seems like it all started with McDonald’s introducing their first iteration of an AI-powered drive-thru in Fort Worth, Texas. Of course, as the first of its kind, it definitely had its issues and garnered plenty of bad publicity. But, that didn’t stop other fast food franchises from rolling out their own AI-powered drive-thru windows shortly after. McDonald’s also plans to double down on their AI-powered drive-thru with a Google partnership for their generative AI needs in 2024 where they intend to use AI for more than just taking your order.

Personalized Experiences

Do you know how every time you open up Amazon, it remembers what you were last looking for and recommends similar products? Well, that’s called a personalized user experience.

Basically, it uses a machine learning algorithm to understand your purchasing and browsing habits to recommend related categories and products that you might like. They use data from other users as well to group similar users together. This gives Amazon a huge data set to analyze for any individual user which creates surprisingly good recommendations. Amazon even sells this as a tool called Amazon Personalize for other eCommerce businesses to deploy.

Fraud Detection

Modern fraud is a lot more complicated than a snake oil salesman who needs to be run out of town. Financial organizations need to actively track the buying characteristics of their customers to identify suspicious activity that could be fraudulent. But, they also don’t want to send out false positives that freeze one of their customer’s active cards. This problem is very expensive as well with credit card fraud costing Americans nearly $250 million in 2023 alone.

As a result, academic and industry professionals have been pushing the capabilities of deep learning models to accurately identify fraudulent transactions while minimizing false positives. So far, these models are experimental. That means we can’t fully know how well they will work until financial institutions start putting them into practice.

The Growing Impact of AI Technologies

Although AI technology has been around for a while, it only hit the main stage at the end of 2022 when OpenAI released ChatGPT. In just a year, we’ve seen massive industries adopt AI technologies for everything from healthcare and fraud protection to fast food drive-thrus and online shopping. That’s a pretty massive change when you consider that before ChatGPT most people thought of AI as a Sci-Fi dream. We can only hope that responsible AI development will continue to make everyone’s life better.

References

Gu, K. (2022). Deep Learning Techniques in Financial Fraud Detection. ICCSIE ’22: Proceedings of the 7th International Conference on Cyber Security and Information Engineering, 282–286. https://doi.org/10.1145/3558819.3565093.

Consumer Sentinel Network (2023). Data Book 2023. https://www.ftc.gov/system/files/ftc_gov/pdf/CSN-Annual-Data-Book-2023.pdf.

McDonald’s partners with Google on AI and cloud technologies (2023), The Verge, 6 December. Available at: https://www.theverge.com/2023/12/6/23990900/mcdonalds-google-ai-cloud-generative.

Kasym, M. (2023). How Much Personalization Is Enough in UX Design?, UX Magazine. Available at: https://uxmag.com/articles/how-much-personalization-is-enough-in-ux-design.

First-ever McDonald’s served by robots opens in Texas (2022), Newsweek. Available at: https://www.newsweek.com/first-ever-mcdonalds-served-robots-texas-1769116.