I probably hate technology terminology as much as you do.

New terms. Meanings change. Terms go obsolete. Repeat.

One of the biggest and most confusing terms right now is “GenAI” or “Generative AI.”

It sounds WAY more complicated than what it actually is—but it’s a term you should understand.

When I first started playing with computers in the 80s, I came across “Eliza.”

It was the first “AI” therapist.

The program was rudimentary and the responses were not that intelligent, but we started seeing the seeds of what we have now.

You could enter questions or statements and it would use a basic “algorithm” to respond with semi-intelligent responses.

You could sorta kinda consider this to be AI—not like we have today, but it had a tinge of intelligence.

How is Generative AI different?

Generative AI simply refers to AI that can generate NEW content.

That’s all it is.

ChatGPT, Claude, Gemini, DeepSeek.

They’re all GenAI.

Traditional AI has been more focused on using machine learning for things like:

• Classifying products

• Looking for patterns in genomes

• Finding trends in data

In traditional AI, we look at existing data and simply extract patterns from the data.

Anything that is generated already exists in the data.

Even though the patterns are “new,” technically they already exist in the data.

GenAI is all about using EXISTING data models to create NEW content.

It’s exactly what you’re using when you ask ChatGPT to write you a social media post.

GenAI is creating a social media post that has NEVER existed before.

So it’s not a special type of AI.

It’s just a term used to distinguish its creative capabilities from traditional machine learning AI.

So when you hear the term GenAI, don’t think about some new technology running no a crazy massive supercomputer sitting in the NSA.

It’s just a fancy word for the same technology you’re already using every day.

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