In this lesson, we are going to talk about use cases for LM applications by industry.
So.
First of all, I wanted to tell you what can lm do?
LM do right.
So you already know ChatGPT.
Probably.
And you know that with ChatGPT, you can create content, you can answer questions, you can read and
summarize documentation, you can have a conversation, etc..
Right.
So how do we apply all these things in real life, for example, when we are talking about content creation.
A what can we do in the business world?
Well, we can translate content.
We can create content for marketing, for sales, for different areas.
We can, uh, use, uh, this functionality for brainstorming.
For example, we are going to see real example in real examples in different industries.
When we are talking about the reading capability of the LM, we we are talking about, uh.
Tool, an application that can summarize documents for us, that can prove reading our documents, that
can analyze our documents, etc. we will see a practical applications of this in different industries.
When we are talking about the conversational functionality of LMS, we are talking about a the possibility
to interact with humans, the possibility to interact with software applications.
And we can have, you know, this a m lm application that.
Is totally autonomous in the conversation with customers, for example, or that is working in a collaboration
with humans.
For example, we can have a chatbot that starts the conversation with a customer and solves the problem.
If it is a simple problem or escalates the problem to a human.
If the problem is complex, right?
So we have this possibility conversation and we will see use cases of it.
Then we have the different types of A applications.
In some cases you will see that a some LM applications A have just a user interface, you know, and
they are pure LM applications with a user interface.
That's all.
In some other cases, you will see that the LM application is part of a bigger software application.
And this is growing a lot.
And during the during the last months okay.
So you see that there is a whole universe universe of possibilities.
But let's see some examples, some real examples by a industry for example.
In the software development industry.
This is one of the industries that has been changed the most during the last year.
Uh, we are, uh, an example of that.
Uh, we have changed totally how we do things by the use of artificial intelligence in our, uh, tech
consulting firm.
So right now you can use Elm applications for learning to code.
For problem solving around your, uh, code or program skills for code creation.
And for code review.
So today, every software developer or software engineer or whatever you want to call these professionals,
we work with an artificial intelligence assistant every day.
The whole day, from the moment we start working to the moment we finish our day.
We are working with a junior developer developer assistant, which is our ChatGPT for or GitHub Copilot
or many other tools.
So you have right now in the market many artificial intelligence tools, which are LM applications,
helping software developers to do our job.
And because of that, we are able to work faster.
We are able to work with many different programming languages.
We are uh, instead of, uh, have everything in our heads.
We can rely on the advice and the help of these assistants.
So our job as software developers has changed.
Absolutely.
And by the way, if you are a software developer or a software engineer and you are still not using
an artificial intelligence assistant, be careful because you are a obsolete a.
The new software engineer is working on a daily basis with an artificial intelligence assistant, and
you will see the difference immediately in your work.
Okay, so in the software development industry, huge change in the customer service industry or department,
also huge change.
We are using LM applications to answer questions about products and services and to solve customer problems.
In most cases, the LM application is helping the human.
The employee is not replacing it in the customer service area.
Okay, so we have in the documentation you have a specific cases like Google etc. and using this uh,
approach.
In the sales industry or the sale the sales area.
We are using applications for qualifying leads to generate sales proposals even to close business deals
in most cases.
Elm applications today are helping the sales professionals in these tasks are not replacing them.
So here you see a case like Salesloft for example, that is, using an Elm application to qualify leads
to generate personalized sales proposals to track customer engagement and to measure the effectiveness
of sales campaigns.
These are real case.
You will see more than that in the marketing industry or marketing departments.
We are already using Elm applications to create personalized content like emails or social media posts.
This is changing the way marketing departments are working, in the same way that sales departments
are totally changing the way they work because of Elm applications.
So you have here some real cases, like Frazee, for example, which is using Elm applications to personalize
subject lines and the body of marketing emails.
In the media and entertainment industries we are already seeing.
LM applications to generate creative content for scripts, poems and code.
So you have companies like OpenAI that has created a range of LM models that create text, translate
languages, create different types of creative content, and answer questions.
In the education industry.
We have companies using LM application LM applications to create personalized learning experiences for
students.
We have the Khan Academy, we have the Newton Company, which is using LM applications to generate custom
problems and tests for their students to create student work and also to provide feedback.
In the healthcare industry.
We are already seeing companies using LM applications to analyze medical histories and to assist in
diagnosing in diagnosing health problems.
In the legal industry.
We are already seeing companies using LM applications to analyze legal documents and to assist lawyers
in their research work.
In the finance industry.
We are already seeing companies using LM applications to analyze financial data and to make investment
predictions.
We will see one particular example of this in detail in our program a real case professional case,
a professional case using an LM application for a financial data analysis, and also investment predictions
and all that.
In the public administration.
We are already seeing the use of LM applications to analyze public documents, to analyze citizen sentiment,
and to improve citizen engagement.
Public administration is one area which is going to have a huge, huge a.
Cases of huge number of cases of LM applications in the automotive industry.
We are already seeing companies using LM applications to improve systems of autonomous vehicles, to
improve voice assistance, to streamline the manufacturing process, etc. so our relationship with the
car is going to change dramatically with the use of LM applications for everything, for maintenance,
you know, repairs, diagnosis of problems, etc..
In biotechnology, we are already seeing companies using LM applications for protein design research
for new drugs.
Bioinformatic research.
Etc. you will see the real cases in the documentation in the energy industry.
We are seeing a lot of applications being used to optimize energy consumption for predictive maintenance
in energy production companies, and also to streamline to streamline operations in the energy sector.
In the research industry, we are seeing l'um applications being used to analyze large databases and
to identify patterns and trends.
So.
You will see in all the documents you have attached to this blog.
A lot of real cases for LLM applications in different industries.
Take a look also at our blog in AI accelerator.com.
Also the book, you know, 100 AI startups.
You're going to see a lot of real cases.
And it's amazing how fast this change has happened because we are only we are.
This is the first year of applications and they are already in most or all industries and professions.
But the interesting thing is that.
Only the most innovative companies and professionals are introducing live applications.
99% of companies and professionals are still not using any application, so there is a huge opportunity
for you to help them understand the potential and to help them, uh, have these solutions built by
you or by a companies that are working with you.
Okay, in the next lesson, we are going to talk about use cases for LM applications in startups.
Super interesting topic because startups usually show the way to the big companies.
So even if you are not working in a startup or you are not interested in creating your own startup,
it is going to be super interesting for you to see what is happening in the startup world.
Because you are going to find interesting inspiration for your work in your company, your work as a
consultant, you know, your work in public administration, whatever.
So startups are leading the way in experimenting, innovating, trying new things, etc. so it will
be very interesting what we are going to see in the next lesson.