In this lesson, we are going to talk about the most frequent use cases for LM applications.
By the end of the year 2023.
Which was the first year of L.l.m. applications.
A many.
AI engineers.
Artificial intelligence engineers were together in the first International Summit of Artificial Intelligence
Engineers that took place in San Francisco.
And one of the things that they did was to fill a survey about, you know, different practices and
the tools they use.
And one of the questions was about the.
LM applications they were using in their companies.
So the result of this survey is not super scientific because the group was not very big, but it is
indicative of what the most.
Expert AI engineers are doing with LM applications.
So the top use of applications for these AI engineers was code intelligence and generation.
So they are using LM applications for software development.
In the second place it was structured data extraction.
A I was telling you about the data analysis and helping data analysts.
So this this second use case is about that.
In the third place we have text summarization.
In the fourth place, we have workflow and app automation.
In the fifth place, we have written assistant and content generation.
Six sentiment analysis seven chatbots.
Eight metadata generation nine search and recommendation systems ten fraud, threat and anomaly detection.
So these are real cases.
A of l'hum application use, but in this case we are getting these answers from the most expert AI engineers
in the world.
This was a small group, was less than 1000 people, but still it's relevant and interesting.
Remember the first one?
Code intelligence and generation second.
Structure data extraction third.
Text summarization.
Fourth workflow and app automation.
Fifth writing assistant and content generation.
Sixth sentiment analysis.
Seventh chatbots.
Eighth metadata generation.
Ninth search and recommendation systems.
10th fraud threat and anomaly detection.
Very important to note that we made here.
This is the year one of LLM applications.
We are seeing LLM applications in most industries, in many professionals, in many professions and
in many startups.
But this is just the beginning.
A we are going to continue seeing this explosion during the next years.
So you are in a very good position to take advantage of this trend.
In the next lesson, we are going to talk a little bit about use cases for LM applications by autonomy
level.
And this is just an excuse to talk a little bit about agents.
So agents are one kind of LM applications that has a have been very popular during the last year.
And it's interesting for us to talk a little bit about a the reality versus the expectations in this
in this area.
So let's talk about that in the next lesson.