After months of trying to come up with a simple and sufficient definition for generative artificial intelligence, it’s time to take on the even more challenging task of defining the next big tech trend…

Quantum computing.

Even though it has been largely overshadowed by the AI feeding frenzy, there has been a lot of recent buzz around this field, which has frustrated innovators for decades. Breakthroughs by both established tech giants as well as promising startups are starting to push quantum computing back to the main stage.

Most notably, IBM recently successfully calculated an Ising Model that simulated the behavior of 127 magnetic particles within a magnetic field using their 127 qubit Eagle processor.

This was an unprecedented feat for IBM, who has a storied history within quantum computing and a record of firsts within the field.

Impressive? 

Sure. But what does any of that even mean?

Qubits? Ising Models? Even “quantum” itself is difficult to define.

If someone ever tells you they totally understand quantum mechanics, it’s safe to say that they don't understand it at all.

Plato said it best. “All I know is that I know nothing”.

Even Albert Einstein described quantum entanglement as “spooky action at a distance”.

If Einstein couldn’t explain quantum mechanics to a novice, then it’s probably not something you should be expected to learn in an afternoon from an e-letter. But quantum computing is coming fast and it will soon be everywhere, so I’m going to try my best to answer the question…

What exactly does “quantum” mean? 

Defining The Undefinable

Here’s the best way I can explain the basics of quantum mechanics as it relates to quantum computing, as I wrote in a recent Technology Profits Daily…

“The two important principles that quantum computing attempts to take advantage of are superposition and entanglement. Superposition is the ability for a particle to be in two different states at the same time. Entanglement is two particles sharing the same state at the same time.”

While I understand that this is how quantum mechanics work, it definitely falls well short of explaining how quantum mechanics work. I challenge anyone to explain exactly what being in “two different states at the same time” looks like.

Which, coincidentally, ties in well to the first logical stop in trying to figure out exactly what anything means. The Merriam-Webster definition(s) of “quantum”...

Noun

a: any of the very small increments or parcels into which many forms of energy are subdivided

b: any of the small subdivisions of a quantized physical magnitude (such as magnetic moment)

Adjective

– large, significant

So quantum means both “very small” and “very big”. Fittingly the word itself occupies two states at the same time.

The more you try to pin down the definition of quantum mechanics, the further you seem to get from understanding what it actually is.

Which makes it a very appropriate way to define the theory.

At the center of quantum mechanics is the uncertainty principle, which in short means that you can not know both the speed and position of quantum objects, or anything with wave-like properties.

In fact, the more you drill down on a wave’s location, the less you know about its speed. The more accurately you measure a wave’s speed, the less you know about its location.

Imagine a cart on a rollercoaster…

On the left, you see exactly where the cart is but it could be stopped or going 40 miles per hour. There’s no way to tell. On the right, we can tell it’s moving quickly but it’s much harder to say exactly where the cart is.

An important thing to know about the uncertainty principle, which was originally presented by Werner Heisenberg, is that it’s not a shortcoming or inaccuracy. Uncertainty is inherent within waves, so an accurate measurement would have to be uncertain.

So do you understand how quantum mechanics work now?

I didn’t think so. But hopefully it’s a little less - as Albert Einstein would put it - scary.

With that, we’d like to hear your thoughts. Do you understand how quantum computing works now? If so, please send us an explanation we can share with future readers at feedback@technologyprofits.com.