What Is Quantum Computing?
Quantum computing (or
as it’s usually called, “QC”) is the process of simulating and demonstrating a
computational model that functions in some way similar to how computers
function. In other words, we want to simulate a model for which there are no
known exact answers. Instead, we make guesses about the answer, and attempt to
run the model efficiently enough so that it can solve problems. This allows us
to compute many things that would otherwise be impossible or difficult to do
with classical computer computing.
What Do We Use It For?
QCs are pretty much useless in their current form. They’re
just another tool to use in our toolbox as someone who wants to get ahead. But
let’s look at how they work for an example. Let’s say you have a problem where
you want to determine whether an email is spam or not. The usual trick used by
humans in spam detection is to look at a bunch of emails and see if the content
matches a certain rule that defines what spam is. Of course, this can be done
manually, but does anyone really like that method? Humans simply don’t like it.
So, instead, we build a system that has a database of hundreds of thousands of
messages and tries to guess the answer. One computer tries to guess that the
email is spam, while another guesses that it isn’t — sort of like when two
people think alike and have the same idea but each one says something
completely different. These systems are often very good at this kind of thing.
Now imagine instead that you had an automated machine
learning system that looked at all the data and figured out the truth about the
question. You could say that when the machine learning system sees an email
that looks like gibberish, it thinks it’s spam. A human wouldn’t even have to
decide that the message is spam, it’d be obvious from looking at it right away.
This type of system might work great for spam detection. An AI could be used to
predict what your next move will be, based off your past history and current
situation. It could also suggest products you should buy based off the
prediction. All of these examples show up in the movie Forrest Gumps, where an
artificial intelligence gets upset with an agent named Jules for saying something
that is wrong but never stops. That AI was able to tell that the person wasn’t
telling the truth, but still gave people credit points for being honest. If
Jules’ prediction were wrong, then he could get some money from the government
or something. He can always figure out the best reply to any situation.
The difference between a regular machine learning
algorithm and QCG is that a regular machine learning algorithm uses training
data that has already been fed into it before taking action, whereas with QCG
it takes action upon seeing an environment and gives feedback before it learns
anything new.
In fact, quantum algorithms have been around since the
60s, but we know that it has only ever been used for problems that involve
qubits or multiple qubits. According to Wikipedia, Qubits is the most accurate
term for the phenomenon at hand.
When talking about QCG, people tend to write “quantum internet”. However, it is unlikely that you will use it for every single task (if you do, go to my article on using it for everything). You use it as a general-purpose tool to help you learn better. Most likely you’ll see it going through things like figuring out what word to put in front of that picture of your girlfriend, or when to give her a date night. When I teach you how to ride a bike, we’re making predictions, because you already know which way you should go. Many people say that quantum computing is too hard to use for basic tasks, but I’ve learned to love it just for figuring out the answer. After all, when you’re going through life, you’ll have tough decisions to make.

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