In this lesson, we are going to talk briefly.
About classic programming versus artificial intelligence.
The faces of the science of artificial intelligence in the last years.
The faces of artificial intelligence applications.
Old artificial intelligence versus new artificial intelligence.
And finally we will talk about how important is the new artificial intelligence right now.
Since the launch of ChatGPT, not a single day has passed without artificial intelligence being on the
front pages of all media outlets.
We read in the media, like the Wall Street Journal, about the $900,000 salaries of new artificial
intelligence engineers.
The terrifying reports from Goldman Sachs about the impact of artificial intelligence on employment.
Or about the overwhelming reservations for the first International Artificial Intelligence Engineers
Congress in San Francisco.
But what is artificial intelligence?
If it has been around for so long.
Why is it interesting now and beyond headlines?
What is its real significance?
It is important to understand that at the end of the day, artificial intelligence is a new way of programming.
Classic programming is, in a sense, like a cooking recipe.
A if we want to prepare whatever a paella, for example, we just have to follow a number of steps.
Step one.
Step two.
Step three.
That is more or less classic programming.
Artificial intelligence is a new way of programming.
Instead of giving the computer different steps in order to achieve one result, we give the computer
the result and ask for the process in order to get that result.
So we give the computer the EPA and we ask, okay, now prepare another by yourself.
We have seen a number of faces.
In the artificial intelligence evolution during the last 50 years.
Believe it or not, artificial intelligence is.
Very old.
It.
It started with what we call now machine learning, which is this different way of programming computers.
Instead of step by step, we provide the result and then ask the computer to find the process to get
that result.
That methodology was invented many years ago, but it was 30 years ago with the internet explosion that
suddenly machine learning engineers had millions and millions of data to work with.
So we started talking about big data.
Data science and machine learning started to be started being more and more accurate, more precise.
Because the more data you have, the more precise it's going to be.
Your prediction.
Um, with the new inventions like neural networks and the GPUs, for example, we started to have a
different kind of machine learning with much more data and much more computational power.
And instead of calling it machine learning, we started calling it deep learning.
And it started to prove really powerful.
And we started doing interesting things with images, with, uh, numbers, etc..
It was just a few years ago when all this promising situation changed in a really important way.
It was with the invention of the Transformers.
Transformers is a methodology that.
Started the generative artificial intelligence movement.
Suddenly, artificial intelligence was a new thing.
We will talk about it very soon.
And with the new Transformers, we immediately started seeing things like GitHub, copilot, ChatGPT,
Midjourney, etc..
And at this stage we are able to start talking about the new stage of the artificial intelligence.
Movement that we ourselves call the new stage of the artificial intelligence.
You universalization, because artificial intelligence is going to be everywhere.
So let's talk a little bit about the stages in the development of artificial intelligence applications.
Before Transformers before generative artificial intelligence.
Building AI applications in a company require skills from machine learning engineers, software engineers,
product managers, and until now, all these skills were learned in separate programs for different
professionals.
So you wanted to create an artificial intelligence application.
You needed a team of different professionals.
Now integrated programs like the one you are studying are emerging to train the new artificial intelligence
engineers.
So we are going to talk about this huge change before in the old artificial intelligence stage.
We needed different professionals to build one application.
Today, we have integrated programs that are going to give you the skills in order to build an artificial
intelligence application by yourself as an AI engineer.
Artificial intelligence applications can be of various types, types, images, video, audio, numbers.
But the universalization of the artificial intelligence comes mainly from what we call LM applications.
Which will soon evolve to become the new multi-modal applications.
So in this course.
They are going to learn about artificial intelligence.
We are going to build a you are going to learn about artificial intelligence, application development,
and in particular the development of the most important kind of artificial intelligence applications,
which are the LM applications.
We will talk more about this later.
So.
As you are seeing.
There is a very important transition between the old artificial intelligence and the new artificial
intelligence, and this has been very recent.
We are going to talk about this in the next lessons.
But right now a couple of notes.
First of all, the all artificial intelligence a.
Provided descriptive results.
The new artificial intelligence.
The generative artificial intelligence is providing creative results.
So the old AI.
For example, is label is labeling an image as cat or not cat.
So it is going to provide the descriptive results based on interpreting or categorizing existing information.
This is the most typical artificial intelligence application.
You give the computer different photos, different images, and the computer can predict if the.
Picture is about a cat or is not about a cat.
So is a descriptive application, but in the new artificial intelligence.
The computers are capable of producing new and original information, like like writing a paragraph
about cats or generating a new image of a cat.
So we are crossing a very, very new bridge here.
And in terms of the typical applications we have in old AI versus new AI, we have a very different
kinds of applications now.
The traditional artificial intelligence applications were about recommendation systems, predictive
analysis, image classification, etc..
The new artificial intelligence applications are advanced chatbots, virtual assistants, content generation
like text, images, music simulators, etc. so we are talking about a very different methodology and
a very different kind of applications.
What is the importance of artificial intelligence?
What is the significance of the new artificial intelligence right now?
There is a wide consensus about among.
Every business leader about every international consulting firm.
About every university professor.
That the new artificial intelligence is the greatest opportunity to create value in our time.
I repeat.
Excuse me.
There is a consensus, a huge consensus in the business, in the consulting firms, in the universities,
that the new artificial intelligence, what we call generative AI, is the greatest opportunity to create
value in our time.
And at the same time, it is the biggest threat to many companies and jobs.
Therefore, you are living in a very exciting times and you are right now.
In the forefront of this exciting times.
You are making a very interesting move for your future.
Remember what top business leaders say about generative AI.
Elon Musk.
Generative AI is the most powerful tool.
Ever created, it has the potential to unleash a new era of human innovation.
Mark Zuckerberg, founder of Facebook.
Generative AI is key to solving some of the world's biggest problems like climate change, poverty and
disease.
Bill gates, founder of Microsoft.
The new generative AI has the potential to change the world in ways we can't even imagine.
It has the power to create new ideas, products and services that will make our lives easier, more
productive, and more creative.
In this lesson, we have seen very briefly what we are going to see in more detail in the attached materials.
We saw the difference between classic programming and artificial intelligence.
The different phases that the science of artificial intelligence has been overcoming.
The different phases to develop artificial intelligence applications.
The difference between all artificial intelligence and new artificial intelligence.
And how important is the new artificial intelligence?
In the next lessons, we are going to start seeing the changes that artificial intelligence is introducing
in different areas.
Jobs, businesses, startups, society.
We will see that everywhere you look.
Artificial intelligence is introducing opportunities and threats at the same time.
So it is very interesting to be in your position right now.
You are going to understand what is happening, what will happen, and you will be in the best position
to take advantage of this new revolution.