Types of artificial intelligence: an analysis from experience

Hello, I'm Ruben Aguila, and I've spent a lifetime watching intelligent machines evolve. From the first rudimentary systems to the technological marvels of today, I've been lucky enough to come across many types of artificial intelligence. In this article, I'm going to explain them all clearly, but with my personal touch. Because here you won't come across bombastic theories that you don't understand; here I tell you what I've lived and learned.

What is artificial intelligence (AI)?

Before we get into the subject, let's agree on something. Artificial intelligence is the ability of a machine to perform tasks that normally require human intelligence. That is, to understand, reason, learn and adapt.

And beware! We are not talking about robots that are going to conquer the world (for now). There are different levels and types of AI that serve very specific things and others that look like something out of a science fiction movie.

The types of artificial intelligence: everything you need to know

Let's cut to the chase. There are several ways to classify artificial intelligence. The simplest divides it into three types:

Narrow AI (or limited)

Narrow AI (or strong)

Super artificial intelligence (ASI)

1. Narrow AI (Narrow AI)

This is the type of artificial intelligence you interact with every day without realizing it. It's like a specialist: it only knows how to do one thing, but it does it well.

For example:

Virtual assistants like Alexa or Siri.

The recommendation systems of Netflix or Spotify (which know which movie or song to suggest to you better than your friend).

Medical diagnostic algorithms that identify diseases in X-rays.

But here's the kicker: they don't understand anything outside their field. For example, Alexa can't solve advanced mathematical equations or answer philosophical questions. She's good at her thing, period.

2. General AI (AGI)

Here's where it gets interesting. Have you seen the movie Her or Ex Machina? General AI is that one that can think, reason and learn like a human being.

We're still far from having real AGI, but it's the dream of researchers: a machine that can perform any intellectual task a human does, from writing poems to solving complex engineering problems.

Personally, I think when we get to this, the world won't be the same. But it's also scary, don't you think?

3. Super artificial intelligence (ASI)

This is the future (and also the setting for our biggest nightmares). ASI would be an intelligence that surpasses human intelligence in every aspect, including creativity, problem solving and decision making.

Imagine a machine that not only surpasses Einstein in physics, but also writes novels better than Cervantes. But beware, it could also decide that we humans are a hindrance, as we have seen in movies like Matrix. Are we ready for something like that?

Types of AI by functionality

Another way to classify AI is by how it works:

1. Reactive AI

It is the simplest. It makes decisions based only in the present, without learning or remembering. A classic example is Deep Blue, the program that defeated Kasparov in chess.

It does not learn, it does not feel, it does not think. It simply calculates.

2. Memory-limited AI

Here we are talking about something a bit more advanced. This type of AI learns from the past to improve its performance. Autonomous cars are a great example: they analyze real-time data (such as traffic) and also remember past situations to avoid accidents.

3. Theory of mind

This type of AI is still under development. The idea is that it understands human emotions, beliefs and needs. It would be like talking to someone who really understands you.

4. Self-awareness

The holy grail of artificial intelligence: a machine that is aware of itself. For now, this is the realm of fiction, but research is advancing rapidly.

The main approaches to AI

When we talk about how AI is built, we find two major approaches:

1. Symbolic AI

It's like solving a puzzle using rules and logic. This approach is perfect for expert systems, which are used in medicine or law.

2. Connectionist AI (deep learning)

Have you heard of neural networks? This approach attempts to mimic the human brain using mathematical models. This is where deep learning comes in, enabling things like facial recognition and natural language processing.

Current AI applications

AI is everywhere, and if you don't believe me, here are some examples:

Medicine: imaging diagnostics, disease prediction.

Transportation: autonomous cars and traffic management.

Marketing: customer segmentation, personalized recommendations.

Education: platforms that adapt to your learning pace.

Entertainment: recommendation algorithms on platforms like YouTube.

Conclusion: Where are we going with artificial intelligence?

AI is not a fad; it is the future.

And while it has risks - such as unemployment or loss of privacy - it also offers incredible opportunities to improve our lives.

The important thing is that we understand how it works and its implications. So, I hope this article has helped you see things more clearly. And if you ever have to face a robot, remember: we're still better at emotional chess.