In this lesson, we are going to talk about what it is an LM application.
The best way to understand what it is an LM application is to look at some of them in our website.
AI accelerator com slash hyphen use cases.
You will find a lot of articles talking about LM application real cases in the book 100 AI startups.
You can also find a lot of real cases of LM applications that are making more than $500,000 in their
first year.
So it's very good for you to get familiar with all these real cases.
We are going to talk more and more about them in the next lessons, but it could be good for you to
take a look at them right now.
And you will see that during this course, we are going to use the analogy of the engine and the vehicle.
Many times.
So the most important thing for you to understand is that an LM application is an app on top of what
we call foundation LMS.
So we will talk more about a foundation LMS later.
But just for now, think of.
ChatGPT as one foundation.
LM so we are going to build applications on top of.
ChatGPT and other foundations.
Okay, so this is an LM application, an app we build on top of a foundation LM model like ChatGPT.
And this application can be on the web, mobile or whatever.
Robotics whatever.
So the analogy of the engine and the vehicle is something, as I was telling you, we are going to use
often.
So the foundation LM like ChatGPT ChatGPT is a foundation LM we will learn more about that later.
But the foundation LM is like an engine, and the LM applications are like all the vehicles and machines
that use the engine to do things like the cars we build with the engine, the trucks, the boats, the
industrial machinery, etc..
Okay, so right now just think about LM applications as these vehicles we build on top of the engine
of ChatGPT.
Okay.
Very important thing to keep in mind as well right now is that LM applications are only one year old.
So they are very, very young.
This means that probably they are going to evolve.
They are going to change a lot during the next years.
So what we know right now for LM applications probably are going to be obsolete in three, four years.
The same thing happened with the internet applications, the initial internet applications.
So the important question for you to understand is how to develop LM applications.
And the kind of LM applications we are going to build is going to evolve a lot during the following
years.
So we don't know where will we use LM applications in five years.
We know where are we using LM applications today and in the following year, that's for sure.
But we will see about the evolution of LM applications.
But right now main concept A use this analogy of the engine and the vehicle.
And also start getting familiar with examples of real cases in our website AI accelerator comm.
And also in the book, 100 AI startups are going to see a lot of real examples there.
So in the next lesson, we are going to talk about the myth of the prerequisites for learning a program
like this one.
Especially the second part, because since we are going to start talking about.
Some technical concepts.
It is very frequent that people get scared.
The non-technical people get scared and think that this program is not for them.
That is not the case, and it is important for us to talk a little bit about all these myths about the
prerequisites for learning programs like this.
So we are going to talk a little bit more about that in the next lesson.