While ChatGPT revolutionized the world and brought us closer to AI, there are many different types of AI that we already use and have no idea about. Therefore, in this article I have discussed different types of artificial intelligence technology, their applications and current examples. From AI chatbots to email spam filtering algorithms, I’ve covered them all. On that note, let’s look at different types of AI technology.
1. Narrow AI (Weak AI)
Let’s start with Narrow AI, also known as Weak AI, is a type of artificial intelligence technology that excels at specific tasks. These types of AI systems are designed to perform tasks for which they are trained and cannot operate beyond their capabilities. They do not have the ability to learn new skills and transfer knowledge to other domains.
Narrow AI systems typically require human intervention for new tasks. To give you an example of Narrow AI, email spam filtering algorithms are trained to classify emails as important or unwanted. As you can notice, this kind of AI technology is only designed for spam filtering and cannot do anything else. Similarly, facial recognition systems that rely on CNN (Convolutional Neural Network) can only identify and match individuals based on facial features.
Although Narrow AI has a narrow focus and requires different AI systems to be trained for different tasks, they are still very powerful. It has transformed many industries, including healthcare and finance, with faster and more efficient performance.
2. Artificial General Intelligence (AGI)
Artificial General Intelligence or AGI is a type of AI technology that can match human cognitive skills for a wide range of tasks. Unlike Narrow AI, which can only perform a specific task, artificial “general” intelligence is more general in the sense that it can perform tasks for which it has not been explicitly trained. In short, AGI systems can understand, learn and apply knowledge across domains.
Note that this type of AI technology is still theoretical and researchers claim that we can achieve AGI in the next five to ten years. Currently, large language models such as ChatGPT and Gemini are still considered Narrow AI because they cannot learn new skills outside of their training. Plus, they don’t really understand the world like humans do.
3. Artificial Super Intelligence (ASI)
Artificial Superintelligence or ASI is the next type of artificial intelligence technology that can surpass human intelligence in every possible way. In short, it is the next step of AGI and can surpass human capabilities in creativity, problem solving, general wisdom and more. ASI systems will have cognitive abilities that can rival even the brightest human minds.
The main characteristic of ASI is self-improvement, which means it can improve itself over time and acquire new skills. In the AI field, this is called continuous learning. That said, ASI is still theoretical and researchers say that once we achieve ASI, we can solve humanity’s biggest problems such as climate change, diseases, poverty, etc. At the same time, many argue that ASI could pose existential risks to humanity and that we need to have conversations about controlling ASI.
Types of AI based on functionality
In addition to broader types of AI, there are several AI systems that can be classified based on their functionality. Here are that kind of artificial intelligence technology.
1. Reactive machines
Reactive machines are the most basic forms of AI that operate without memory. It does not use past experiences to decide future actions. They are programmed to require specific inputs with predetermined outputs. In short, they follow an input-output response pattern. Keep in mind that this type of AI cannot learn or adapt to new environments.
To give you an example, rule-based email filters are reactive machines that check for specific patterns. Likewise, keyword matching systems, or basic recommendation engines, are reactive machines. The IBM Deep Blue AI system that defeated world champion Garry Kasparov in 1997 checked millions of possible moves but had no memory of previous games.
2. Limited memory AI
Limited Memory AI systems are the type of AI technology that learns from historical data and uses past experiences to decide future actions. Most current AI applications fall into this category. It stores temporary information, improves over time, and makes predictions based on past patterns. For example, self-driving vehicles sense traffic, road conditions and the behavior of other vehicles to navigate safely.
Similarly, AI chatbots like ChatGPT learn from previous conversations to provide better answers. Image recognition software is also trained on labeled images to identify new images. These are all examples of Limited Memory AI.
3. Theory of Mind AI
Theory of Mind AI is currently in the realm of a fictional concept. It is a type of AI technology that can understand human emotions, beliefs and intentions. These AI systems could recognize that people and animals have thoughts and feelings that influence their behavior. Based on this emotional context, AI systems can predict behavior.
AI labs are developing robots that can mimic human facial expressions based on emotional state. New research also shows that they can change their voice tone and emotions. It could be useful for mental health support and educational AI systems that can adapt to students’ needs.
4. Self-aware AI
Finally, we come to Self-Aware AI, an advanced type of artificial intelligence. This kind of machine will have consciousness and self-awareness. They will have their own internal desires, perception and understanding of their own existence. Self-aware AI can both process human emotions and maintain its conscious state.
Currently this is a hypothetical AI system, but it raises several questions about what it means to be alive and who we are as humans. Can machines ever acquire consciousness like humans and will they have rights and moral responsibilities? We can only know that in the future.
So these are the different types of artificial intelligence technologies that you can learn. Currently, we only have experience with narrow and memory-limited AI systems. However, the AI field is developing rapidly and by all accounts, we can achieve AGI in the next decade.
