Banksy + Gen AI vs. Traditional AI

Dr. Ryan Ries here, and this week we're diving into a topic that's been coming up a lot in my recent customer conversations: generative AI vs. AI.

But here's the twist — it might not be what you think it is.

The ChatGPT Catalyst

Let's cut to the chase: ChatGPT was the spark that ignited the current gen AI craze.

But why?

It wasn't because it was the first AI model (far from it), or even the most advanced.

ChatGPT's real innovation was its accessibility. Suddenly, anyone could chat with an AI model as easily as texting a friend.

No coding required, no complex setup — just type and go.

This ease of use is what's really driving the gen AI conversation. When customers tell me they want to implement gen AI, what they're often really saying is: "We want an easy way to interact with AI models and just ask questions."

GenAI vs. AI: The Line Blurs

Here's where things get interesting.

In the wake of ChatGPT's popularity, suddenly everything is being labeled as "Gen AI."

But let's be real — not every AI application is truly generative. Some are just good old-fashioned AIs dressed up in new marketing clothes.

The key difference? Generative AI creates new content — text, images, code, you name it. Traditional AI is more about analysis and prediction.

Both are powerful, but they're not the same thing.

A Century of Neural Networks

Now, for those of you who love a good origin story, let's take a quick trip down memory lane.

Believe it or not, the roots of gen AI go back further than you might think:

• 1914: A typewriter that could be considered the first example of gen AI (I know, mind-blowing, right?)
• 1943: The first artificial neurons by Warren McCulloch and Walter Pitts
• 1950s-60s: Early neural network models like the Perceptron
• 1980s-90s: Rise of backpropagation and more complex neural nets
• 2000s-2010s: Deep learning takes off, but still limited by compute power

The Cloud: The Final Piece of the Puzzle

So why did it take until now for gen AI to hit the mainstream?

Two words: storage and compute.

For the past century, we've had the theories, but not the horsepower to make them work at scale.

Enter cloud computing.

The cloud finally gave us the massive storage and computational power needed to train and run these complex models. Without it, ChatGPT and similar AI models would still be academic curiosities, rather than the world-changing tools they've become.

What This Means for You

Here's the bottom line: Implementing gen AI, is really about making AI accessible and interactive.

It's about bridging the gap between complex machine-learning models and everyday users.

As we move forward, I believe we'll see more and more focus on making AI — generative or otherwise — as interactive and accessible as possible.

If I got a dollar for every time I read the words “gen AI revolution”, I’d be one rich man.

But the real revolution isn't just in the technology itself, but in putting that technology at everyone's fingertips.

Let me know what you think about this. Also, if you have any topics you want me to cover in future Matrix newsletters, just reply to me here.

Until next time,

Ryan

PS. Na Yu and Jonathan LaCour are hosting our next generative AI Ask Me Anything event on September 14th. Will I see you there? Bring all your questions!

Now, time for this week’s AI-generated image and the prompt I used to generate it.

"Generate an image of someone using an old school, early 1900s typewriter. The image should be in the style of Banksy."

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