In IT, there is a tremendous amount of jargon.

We are constantly using acronyms and abbreviations and obfuscating meaning.

And, I have to admit, I have used terms without fully understanding their meaning, even though I thought I did

Sometimes, the same terms can have different meanings like the term SASE, which means Secure Access Services edge, and not the Self Addressed Stamped Envelope I would send off to people advertising in the backs of comic books when I was a kid.

One term that is talked about a lot today is AI/ML, as if AI and ML are interchangeable concepts.

But they aren’t.

AI has been around for a long time at least since 1956 when the program “Logic Theorist” was conceived by Allen Newell, Cliff Shaw, and Herbert Simon to mimic human problem solving skills.

By the 1980s experts systems started to show up and in 1997 Deep Blue defeated chess champion Gary Kasparov. Around that time, we started to see speech recognition systems hitting the market.

All of these things were called AI at the time, but by today’s standards they are less than.

So today when we look at the panoply of AI, we see it as an onion.

AI is the outer ring, the general category.

ML, or Machine learning is a ring inside the onion, which uses algorithms to parse data and make predictions.

Deeper into the onion is DL or Deep Learning which utilizes neural networks to perform machine learning on large data sets.

We have reached the age of reasoning machines, and we look down the road to Artificial General Intelligence and Self-Aware Systems.

Perhaps someday, we will become one with the machine intelligence and reach Singularity and Transcendence, but for now we have machines, that one day will seem primitive when we look back, but are doing and discovering amazing things today.

And for now we should take pause and try to understand what we have built, and what it means to society and to future generations, because whatever AI really is, it is inevitable.