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In this lesson, we are going to talk about the most frequent use cases for LM applications.

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By the end of the year 2023.

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Which was the first year of L.l.m. applications.

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A many.

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AI engineers.

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Artificial intelligence engineers were together in the first International Summit of Artificial Intelligence

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Engineers that took place in San Francisco.

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And one of the things that they did was to fill a survey about, you know, different practices and

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the tools they use.

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And one of the questions was about the.

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LM applications they were using in their companies.

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So the result of this survey is not super scientific because the group was not very big, but it is

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indicative of what the most.

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Expert AI engineers are doing with LM applications.

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So the top use of applications for these AI engineers was code intelligence and generation.

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So they are using LM applications for software development.

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In the second place it was structured data extraction.

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A I was telling you about the data analysis and helping data analysts.

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So this this second use case is about that.

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In the third place we have text summarization.

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In the fourth place, we have workflow and app automation.

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In the fifth place, we have written assistant and content generation.

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Six sentiment analysis seven chatbots.

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Eight metadata generation nine search and recommendation systems ten fraud, threat and anomaly detection.

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So these are real cases.

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A of l'hum application use, but in this case we are getting these answers from the most expert AI engineers

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in the world.

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This was a small group, was less than 1000 people, but still it's relevant and interesting.

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Remember the first one?

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Code intelligence and generation second.

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Structure data extraction third.

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Text summarization.

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Fourth workflow and app automation.

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Fifth writing assistant and content generation.

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Sixth sentiment analysis.

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Seventh chatbots.

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Eighth metadata generation.

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Ninth search and recommendation systems.

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10th fraud threat and anomaly detection.

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Very important to note that we made here.

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This is the year one of LLM applications.

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We are seeing LLM applications in most industries, in many professionals, in many professions and

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in many startups.

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But this is just the beginning.

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A we are going to continue seeing this explosion during the next years.

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So you are in a very good position to take advantage of this trend.

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In the next lesson, we are going to talk a little bit about use cases for LM applications by autonomy

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level.

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And this is just an excuse to talk a little bit about agents.

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So agents are one kind of LM applications that has a have been very popular during the last year.

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And it's interesting for us to talk a little bit about a the reality versus the expectations in this

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in this area.

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So let's talk about that in the next lesson.