So in this lecture, I want to address a mistake that I see from time to time when it comes to this
section.
Now, I wouldn't call this a common beginning mistake, since it doesn't seem to be that common so far,
but it has come up and thus I would like to address it.
And if you made this mistake, hopefully this lecture helps you.
OK, so the mistake is that a few students have come to this section thinking that you could use this
technique on modern encryption methods such as RSA now to think about why this is a mistake.
You really just have to think logically, if this method were that easy to crack, then we simply wouldn't
be using it.
Remember that the whole point of using strong encryption is that it cannot be broken using current technology.
So if you thought, Hey, I'm going to just sign up for this random course online, that will teach
me how to break the security that everyone around the world relies on.
There's probably a big hole in your logical reasoning.
Now, at this point, you may wonder if this method cannot break modern encryption methods, then what
is the purpose in learning it?
And again, it's just one of those things that's obvious if you are a student of the subject and perhaps
not obvious if you really don't get it.
It reminds me of students who take my finance courses.
Often in those courses, you get students who sign up to learn finance and they think, OK, so if I
take this course, I'm going to get some code and then I'm going to use that code to become a millionaire
for most reasonable people.
They realize why this is absurd.
Many people learn finance whether to become a quants, to develop their own strategies or to simply
understand how finance works.
These are realistic goals.
Reasonable people are able to separate realistic scenarios from unrealistic scenarios.
And the same goes for this course.
You have to separate realistic goals from unrealistic goals, realistic goals are learning more about
NLP, learning more about machine learning, using this section to gain a deeper understanding of language
models and optimization methods.
Obviously, these can help you in your career, and these are skills that you can apply in your future
work.
People might offer you jobs because you have these skills.
So in that sense, they can lead to a positive return on your investment.
These are different from unrealistic goals.
No, you are not going to crack an encryption algorithm and hack the largest governments and corporations
around the world.
It's simply not going to happen.
So if you were one of those students that made this mistake, then hopefully this lecture helped to
put you back on the right path.