Let’s cut to the chase and answer the question everyone is asking
It’s becoming increasingly obvious that the A.I. bandwagon is running out of room.
It’s time to hop on.
Everybody’s doing it.
Before it’s too late?
Look, maybe you’ve quickly become a Generative A.I. expert. Or maybe you’ve been playing around with GPTs and know enough to be dangerous. Or maybe you have no idea what all the fuss is about.
Should you be using A.I.?
I’ve been developing Generative A.I. solutions for 13 years. I’ll give you a fast framework to answer that question for yourself.
The part of A.I. that makes all the money is not so much about getting the right answer as it is asking the right question.
This new flavor of A.I. isn’t all that new. And it is indeed just a flavor, is not the kind that’s going to kill us all… yet.
In 2010 and 2011, I co-invented the first commercially available Natural Language Generation (NLG) engine and platform at Automated Insights, which is a fancy way to say that we taught computers how to write articles based on data.
While we used both A.I. and machine learning (ML) to enhance the engine and the platform, our product was neither pure A.I. nor pure ML. Since those early days, NLG has been combined with Natural Language Processing (NLP), a science that started going mainstream with Alexa and Siri, and has now evolved to become Generative A.I. — what we think of as OpenAI and ChatGPT and the like.
But back in 2010, the term NLG hadn’t been coined yet, or at least it wasn’t mainstream enough to get on into our consciousness, so we referred to what we were doing as “automated content,” because automation is like 90% of what makes A.I. seem like magic.
So the real question you should be asking is, “How much automation should I use in my business?”
And to get to that answer, we have to understand the difference.