What Is AI?

AI vs GenAI

If someone asks you if you use AI, your initial instinct will probably be to think about whether you use chat tools like ChatGPT, Gemini, Claud, etc. right? It's important to recognize that those tools are specifically Generative AI, or GenAI, for short, but, this is not the only type of AI.

You may have used AI today without even realizing it.

Have you opened your phone with facial recognition?
Have you used Facebook, Instagram, Netflix, spotify or any other application that suggests items you might want to see (posts, movies, music, news)?
Have you selected any of the predictive text suggestions while typing out an email?
Have you used any spellcheck or grammar improvement tools in Google Docs or Microsoft Word?

All of these tools constitute AI - Artificial Intelligence. AI is the invisible engine, or "brain", that runs the apps you use every day.

Not all AI is generative (take facial recognition technology, for example). Not all AI is presented as a chatbot.

AI is being embedded in many of our appliances - from the vehicles we drive to the kitchen gadgets we own.

So, What is AI?

As seen before, we have the issue that when talking about "AI", we might not be talking about the same thing. Artificial Intelligence simply means any machine or code that mimics human intelligence to solve a problem. This ultra-broad definition includes concepts that may not be recognized by those thinking of ChatGPT when they hear "AI". For this reason, it's often better to be explicit in what we mean when we say "AI".

Lets compare modern AI with traditional computing (which is a form of AI):

Traditional Programming: Human written code that explicitly states, step-by-step, what to do. This is a form of Artificial Intelligence, as you're creating something that will act/make decisions on its own, but it can't adapt to new situations without being explicitly programmed to do so. This is known as Deterministic AI or Rule-Based System. It relies on conditions (if ____, then ___) to determine what to do next. It's limited because it can't adjust to new situations and its pattern finding abilities are pretty limited.
Modern Artificial Intelligence: Uses Neural Networks and Machine Learning in order to take huge amounts of data, find patterns, and generate conclusions. It predicts the next step based on what it has seen before.

A common comparison is to talk about learning to recognize a dog.

Traditional Programming method: List all the identifiable traits of a dog (4 legs, barks, facial shape) and use that list to determine whether an animal is a dog. The problem is, because it doesn't adapt, it can't identify a dog that doesn't fit the mold (missing a leg, bark is different, etc.). Adaptations have to be manually made by the programmer.
- This is the type of logic that makes it so we misidentify tomatoes as vegetables, orcas as whales, and koalas as bears.
Artificial Intelligence Method: Show billions of images of dogs, the AI trains itself to identify commonalities. This method uses pattern recognition.

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3 Stages of AI

There's 3 stages of AI that you'll typically hear about.

Stage 1 - Narrow (or Weak) AI

This is any form of AI we have now or have seen in the past. This includes hard-coded AI, but typically we'll focus on more modern generative AI (ChatGPT, Gemini, etc.). This is considered "Narrow" and "Weak" AI because it generally focuses on a single task - image recognition, music generation, cancer identification, etc. ChatGPT and Gemini still fall into this category even though they seem like they can do multiple tasks (image generation, conversations, mathematics, poetry, etc.), but there's often multiple specialized agents that these tools outsource their work to. For example, when I first started using ChatGPT, it had a special bot connected to it called Dall-E that would take care of all the image generation requests.

Stage 2 - Artificial General Intelligence (AGI, Strong AI)

This is a futuristic form of AI where it is capable of doing pretty much everything we can do just as well as we can do it. It learns and adapts to new circumstances. Essentially, it is AI that works just as well as the human brain at pretty much everything. At times, our AI systems feel like we're in this zone - AI can synthesize information from a book significantly faster than I can and it can make connections within the book I likely won't have thought of. But, it may only be trained on that one task and can't learn something new.

Stage 3 - Superintelligent AI

This form of AI passes human intelligence in everything it does. If humanity ever got to this point, this becomes the points where AI leads human advancement (or, according to the Terminator, human destruction).

AI Learning Methods

Supervised - AI is trained on existing, labeled data (AI sees the patterns and uses those to label more data)
Unsupervised - AI is trained on existing, unlabeled data (AI has to figure out what patterns exist on its own)
Reinforcement - AI learns what responses provide the best outcomes/rewards and adjusts, essentially like positive reinforcement in humans.
Deep Learning -
Transfer Learning -

Related Resources

Y Magazine - I Chatbot - How worried should we be about the arrival—and impact—of chatty new AI machines? BYU experts weigh in.

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