What are the types of AI?

What are the types of AI? Understand how they are classified and evolve
From simple automation to superintelligence, see what distinguishes each artificial intelligence model

It's no longer news that artificial intelligence (AI) is behind almost everything we use in our daily lives – from work to leisure, including organizing our home schedule, and so on. This widespread presence is only possible because there are different types of AI, developed to perform specific tasks or to learn autonomously according to their purpose.

What reaches us is the final answer, but each type has its role in the functioning of applications, platforms, and digital services. All this technology forms a complex invisible network that transforms simple data into personalized decisions, predictions, and experiences.

While some are highly specialized and operate within defined limits, others can (theoretically) learn and act with flexibility similar to humans. To understand this universe, experts usually classify the types of artificial intelligence according to two criteria: by resources (or capacity) and by functionalities (or mode of operation). This distinction helps to understand what AI is capable of doing and how far it can go, as we will see below.
Types of artificial intelligence by features

In this aspect, we can assess how well AI can adapt to get close to human reasoning. On this scale, the main types of AI are narrow, general, and superintelligent.

Narrow AI (ANI – Artificial Narrow Intelligence)

This is the current stage of the technology, and also the best known to the general public.

Narrow (or weak) AI is programmed to perform specific tasks with high performance, but within strict limits. In other words, this model is an expert, but it cannot make connections or "think" about the world broadly, because everything it does is based on pre-trained patterns or data.

ChatGPT, for example, is very efficient at answering questions and generating texts, but it could not drive a car or diagnose diseases. Similarly, Gemini is capable of interpreting texts, images, and audio, and performing complex analyses based on them, but it still lacks the awareness to act outside the parameters it has received.

This is the technology that drives AI today, and it's behind streaming recommendations, social media, automatic translators, and even solutions for detecting fraud in banks. Although they don't think like humans, they can automate processes and improve productivity with great precision.

General AI (AGI – Artificial General Intelligence)

One of the most ambitious types of artificial intelligence is general AI, which represents the technology capable of learning and applying knowledge in any area, just as a human being does.

Unlike narrow AI, which needs training for each function, AGI would have the autonomy to transfer what it learns from one context to another. For example, if it learned a new language, it could use that knowledge to understand cultural expressions or correct translation errors in a text. Currently, no AI can do this completely independently.

This type of technology still depends on immense advances in areas such as neuroscience and machine learning. Even with the continuous progress of generative AI models, most experts agree that general AI is still on the long-term horizon.

Superintelligent AI (ASI – Artificial Superintelligent)

If the goal of general AI is to achieve the human mind, superintelligent AI aims to surpass it in cognitive and creative terms.

Theoretically, this is the perfect AI model, capable of mastering areas ranging from mathematics to philosophy, from engineering to art, and so on. In addition to its unparalleled speed in processing information, it would be able to develop ideas not yet conceived by humans.

For now, it is just a concept that arouses fascination and fear at the same time. Researchers and scientists warn of the need for strict limits and safety protocols, as an eventual "hallucination" of ASI could cause unimaginable damage.

Types of Artificial Intelligence by Functionality

While classification by features assesses the "intelligence" of the technology, the division by functionality considers how the AI interacts with the world.

Typically, this approach includes four types of AI: reactive, with limited memory, theory of mind, and self-aware.

Reactive AI

Basically, a reactive AI responds to immediate stimuli according to predefined rules, without storing previous experiences.

A classic example is intelligent traffic lights, which adjust their signals based on real-time vehicle flow, but do not retain memory. They only respond to the moment, as they cannot, for example, "remember" traffic jams or previous traffic patterns.
This type of AI is still very useful in industrial applications, games, and systems that need predictable and quick responses, but do not require continuous learning.

AI with limited memory

This category learns from data and past experiences, and is the most present in our daily lives.

AI with limited memory adjusts its responses based on the information it collects. This is the case with autonomous cars, which improve their driving based on the analysis of traffic, driver behavior, and weather conditions.

The same happens with virtual assistants (such as Google Assistant) and recommendation apps (such as Spotify), which consider the user's history to offer personalized responses.

This type of AI relies on large volumes of data (big data) and machine learning models that improve their usefulness and "intuition" over time.

Theory of Mind AI

From now on, we move on to the models under development. The first of these is Theory of Mind AI, inspired by the human capacity to understand thoughts, emotions, and intentions.

Applied to artificial intelligence, this technology would be able to identify, for example, if someone is sad, confused, happy, or angry and respond accordingly. Research in this area involves social robots and health assistants, but interaction with people is not yet sufficiently insightful.

Self-Aware AI

Finally, self-aware AI would be able to recognize its existence, understand the world around it, and have its own goals. In practice, it would be able to explain the reasons that led it to give a response and even recognize mistakes and learn from them.

Although this type of AI is closer to science fiction than reality, its format serves as a reference for debates about the limits of technology.

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