You don’t have to work in marketing to say that you’ve had first-hand experience with the different forms of AI. While ChatGPT and Uizard get most of the limelight when discussing the various types of AI, many forget that Amazon’s Alexa and Apple’s Siri are also AI types.
We are currently living in the revolution of AI. Its effects are profound in digital marketing but expand into almost every niche, with different types of AI tending to and executing various tasks.
In this article, we delve into the main types of AI to illustrate the significant advancements and influence of AI on informational technology.
Table of Contents
- The Basics: AI vs. Machine Learning and Deep Learning
- The Seven Types of AI
- Narrow AI
- Artificial General Intelligence (AGI)
- Super AI or Artificial Superintelligence (ASI)
- Limited Memory AI
- Reactive Machine AI
- Self-Aware Artificial Intelligence
- Theory of Mind AI
- Artificial Intelligence and the Future
- Types of AI FAQs
The Basics: AI vs. Machine Learning and Deep Learning
Knowing the difference between the three terms above is crucial to understanding how the different types of AI function. Experts usually recommend learning about them as one large tree.
In this example, AI would be the trunk and its most extensive branch, machine learning, splits into several smaller branches. One of those would be deep learning. All three are connected but refer to different processes.
Artificial Intelligence
AI refers to an area of computer science that strives to simulate human intelligence in machines and software. Experts have predicted that AI will be capable of carrying out retail-related tasks, translations, and even performing surgery in the near future. While this is still not the case in 2024, the launch of ChatGPT in 2023 fueled the forecasts further.
Currently, these models cannot match human intelligence. However, they can be effective at carrying out specific tasks, and even outperforming humans in particular areas like data science, or the ability to process huge amounts of data within seconds.
Machine Learning
This term refers to the algorithms that help AI software pick up on data patterns. This is similar to the way humans learn. A good example of machine learning would be movie recommendations based on previously watched films on a streaming platform.
Deep Learning
Deep learning is a type of machine learning in which computer scientists aim to teach software to think based on the way neural networks work in the human brain. For instance, healthcare image recognition is an excellent example of deep learning in practice.
Despite the clearly defined differences, the terms may sometimes overlap. For example, self-driving cars use AI, machine learning, and deep learning to travel autonomously on the road.
In all these cases, programs are capable of learning from experience and examples to take more accurate actions without human interventions, making them all cogs in a bigger AI model.
The Seven Types of AI
Before we get started, we should emphasize that these seven artificial intelligence types are a part of two bigger groups: capability-based types of artificial intelligence and functionality-based types of AI.
The first one is based on how they learn and how they can apply their knowledge. Capability-based AI types are narrow AI, general AI, and super AI.
Functionality-based AI models focus more on how artificial intelligence applies its learning capacity to process incoming data, interact with its environment, and respond to input. In this category, we have four different AI models: limited AI, reactive AI, self-aware AI, and theory of mind AI.
Narrow AI
Also called weak AI or artificial narrow intelligence (ANI), it usually refers to specific AI tools that are created to carry out commands or actions. They are engineered to perform and excel in a single cognitive feature and can’t learn any skills or information beyond their design limits.
Narrow AI mainly uses neural network algorithms and machine learning to complete their delegated tasks. For example, natural language processing is a type of weak AI since it can recognize and respond to voice commands but won’t perform other related tasks.
The best examples of this type of artificial intelligence include image recognition solutions and AI virtual assistants.
Artificial General Intelligence (AGI)
Also referred to as strong AI, AGI is a type of artificial intelligence that has the capability of learning and performing various actions like a human. The aim of designing artificial general intelligence stems from the goal of eventually creating machines capable of carrying out tasks and acting as equally capable assistants to us.
AGI types of AI are still a work in progress, but the groundwork is already here. Such AI types could be built by leveraging the tech of quantum hardware, supercomputers, and other generative AI models.
Super AI or Artificial Superintelligence (ASI)
ASI or super AI are types of AI that are straight out of science fiction. According to theory, once AI reaches general intelligence level, it will be capable of learning faster than humankind. This will lead to its capabilities and knowledge surpassing those of humankind.
Super artificial intelligence would be the base technology for individualistic robots and completely self-aware AI models. It’s also a fairly popular media concept that has served as the core idea behind such long-running franchises as The Terminator. Still, at this point, the future of super-intelligent robots remains speculative.
Limited Memory AI
The first functionality-based artificial intelligence type on our list, limited memory AI, can store past data and use it to make its own forecasts, i.e., predictions. In other words, this form of machine intelligence can build limited and short-term knowledge bases to perform tasks that fall under said knowledge.
Deep learning comprises the core of limited memory AI, which imitates the human brain’s neuron functions, allowing the machine to comprehend the data from its experiences and learn from them, improving action accuracy as time passes.
Today, this type of artificial intelligence is the most prominent you might run into. Having a broad application range, this is the AI model behind self-driving cars and chatbots, for instance.
Examples of Limited Memory AI
Virtual assistants are also limited memory AI types. The more users interact with them, the more they learn from the gathered data. They can then recall specific details about the user, enabling them to provide more personalized and relevant responses.
Another great example would be self-driving cars, which constantly gather and process data from the environment around them as they drive on the road. The processed data helps them predict when they need to stop, avoid obstacles, or turn.
On that note, according to a McKinsey report, by 2030, nearly 12% of new sold cars will have self-driving technologies, and by 2035, 37% of them will have advanced automated driving tech.
Reactive Machine AI
Reactive AI is the most fundamental type of artificial intelligence. As the name implies, this model is only reactionary, responding only to immediate tasks and requests without a robust memory rooted in learning from previous experiences or any functionality improvement over time through learning. Additionally, these systems can only respond to limited input combinations.
However, these technologies may also be helpful in performing simple autonomous functions, like recommending items based on browsing history or filtering out spam mail from your inbox. Reactive models are limited beyond basic tasks, as they cannot build a deeper knowledge base or execute more complex tasks.
Examples of Reactive AI
Netflix’s recommendation engine is a prime example of this form of AI. The machine can process data from browsing and watch history to create a suggestive list of movies the user would likely watch.
IBM Deep Blue was also a reactive machine AI model that famously beat Russian chess legend Garry Kasparov in 1997.
Self-Aware Artificial Intelligence
This is the category of AI that describes self-aware machines. Also referred to as the AI point of singularity, this is one of the ultimate holy grails of AI development. However, some theories (as mentioned earlier) speculate that once AI achieves consciousness, machines may become uncontrollable as they develop a sense of self and the capacity to experience emotions.
An excellent example of self-aware AI would be Sophia from Hanson Robotics. Even though Sophia isn’t fully self-aware, she serves as a remarkable example of the current advancements in AI technology and offers a glimpse into the potential of self-awareness.
Experts are debating whether the future holds promise or poses challenges, as sentient AI presents potential benefits alongside significant ethical and security concerns.
Theory of Mind AI
While this type of AI does not exist yet, the concept behind it entails technologies that will be capable of perceiving and picking up emotions. Borrowed from psychology, the name describes human’s ability to read other’s emotions and predict their actions based on that information.
While the technology remains speculative, ongoing development and research suggest that theory of mind AI could represent the next significant milestone in AI advancement.
Experts argue that the theory of mind AI could bring several positive technological changes, yet it also poses inherent risks.
Mastering the interpretation of emotional cues could take considerable time for AI systems, potentially resulting in significant errors during the early stages of implementation. Additionally, some theorists speculate that once the technology matures, it could be susceptible to manipulation of others.
A great example of this AI type would be self-driving cars, which can perform better than most human drivers, as they won’t make the same mistakes repeatedly. However, if a driver is aware that children often play near the street after school, they will likely slow down as a precautionary measure. This proactive behavior is something that basic limited memory AI models wouldn't perform, but theory of mind models could.
Artificial Intelligence and the Future
While the future remains unpredictable, one thing is evident: various types of AI have revolutionized nearly every industry, introducing unprecedented efficiencies, innovations, and possibilities. From healthcare and finance to transportation and entertainment, AI technologies are reshaping how businesses operate, people work, and society functions.
As these advancements continue to unfold, it's evident that AI will play an increasingly integral role in shaping the trajectory of human progress and innovation.
Types of AI FAQs
What are the different types of artificial intelligence?
The seven most prominent types of AI include narrow, general, reactive, super, limited memory, reactive, self-aware, and theory of mind artificial intelligence models.
Which AI type is the most common?
Currently, limited memory AI models like chatbots and self-driving cars are the most prevalent.
Will AI take over the world?
In theory, artificial intelligence may become fully self-aware and prioritize its needs instead of humanity’s. However, current advancements suggest that it would take a long time to develop a single platform that would become sentient and that by then, humanity will have the necessary ethics and security protocols put in motion to regulate those events that may lead to a catastrophe.
