Fun fact: 87% of organizations worldwide believe artificial intelligence (AI) technologies will give them a competitive edge.
If you’re not using one yet, it’s time to learn how to leverage the technology to streamline your processes, improve your strategies, and grow your revenue. With a variety of AI tools available, however, you may wonder which AI tools will work for your business.
This blog post will go through the different types of AI tools. You can jump into the AI tool type you want to know more about, if you’re pressed for time:
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4 types of AI based on functionality
There are four main types of AI based on their functionalities and how they process data and respond to prompts:
The table below summarizes the four types of AI based on functionality:
| Types of AI based on functionality | How it works |
| Reactive | Reacts and responds to external stimuli or prompts |
| Limited memory | Collects information, stores it, and learns from it for a set period |
| Theory of mind | Deciphers and responds to human emotions |
| Self-aware | Sentient AI that understands human emotions and is aware of its existence |
Let’s go through each one:
1. Reactive AI
What is reactive AI?
Reactive AI is the most basic type of AI in terms of functionality. It reacts and responds to external stimuli or prompts.
Because reactive AI doesn’t store data, it cannot learn from past interactions. It also can’t save information that it can process in the future or remember for the next interaction.
A famous example of a reactive AI is IBM’s Deep Blue AI, which beat world chess champion Garry Kasparov in a six-game match in 1997. The AI could identify the pieces on the chessboard and react with a move.
An example of a reactive AI in marketing is a chatbot that responds with canned statements to specific prompts or questions a user can select. The AI doesn’t necessarily understand the prompts or the questions — it simply responds with an answer that matches the prompt or question.
Bonus Read: Artificial Intelligence vs. Human Intelligence
2. Limited memory AI
Limited memory AI definition
Unlike reactive AI, limited memory AI can store data from the past and use it to make decisions. It can collect information, store it, and learn from it.
However, as its name implies, its memory is finite. The data it has saved cannot remain in its memory forever. As a result, it can’t continuously learn from past and new data.
An example of a limited memory AI is ChatGPT, which has a token (or text fragments) limit. Once your conversation has reached the limit, ChatGPT will not remember your past conversations and will only respond based on the newer conversations you’ve started.
3. Theory of mind AI
What is theory of mind AI?
Theory of mind AI is an AI that can decipher and respond to human emotions. It can also do the tasks of a limited-memory AI.
While reactive and limited memory AI already exist, theory of mind AI is still a concept. In theory, marketers can use theory of mind AI to understand their prospect’s intentions and predict their behavior. It can then create the appropriate marketing messages and responses, thus aiding in relationship building.
4. Self-aware AI
Self-aware AI definition
Self-aware AI is an evolved version of theory of mind AI — not only does it understand human emotions, but it is also sentient and aware of its existence.
Like theory of mind AI, it is a hypothetical AI. It can sense and predict the feelings of those around it.
There is still much to discover about the human brain’s intelligence, so we’re still far from developing an AI similar to our intelligence.
Sophia, a humanoid robot developed by Hanson Robotics, is a preview of a self-aware AI, although Sophia isn’t sentient yet. It can imitate a human’s facial expressions and gestures, and detect faces.
3 types of AI based on capability
AI tools can be classified according to how their capabilities have evolved, how they learn, and how they use the data they’re trained with:
The table below is a summary of the types of AI based on capability:
| Types of AI based on capability | How it works |
| Narrow AI | Designed to accomplish specific tasks |
| General AI | A mostly theoretical AI that can think, learn, and perform intellectual tasks like humans |
| Super AI | A hypothetical AI that exceeds a human’s intelligence |
Let’s discuss each one:
1. Narrow AI
Narrow AI definition
Also called weak AI, narrow AI is designed to accomplish a specific task.
It is built to fulfill and excel in one particular cognitive capability. Thus, it can’t independently learn to perform other actions beyond its scope.
Narrow AI uses machine learning, natural language processing (NLP), and deep learning. Some examples of Narrow AI are the following:
- Virtual assistants like Apple’s Siri
- Chatbots
- IBM Watson
- Facial recognition systems
- Self-driving cars
2. General AI
General AI definition
Also called deep AI, general AI is still mostly theoretical as of this writing. It can think, learn, and perform intellectual tasks like a human. It can even execute tasks that it’s not trained to do.
In theory, general AI can understand language, solve problems, make decisions, and even have feelings. As a result, it can perform creative tasks and activities requiring empathy and intuition.
While general AI can theoretically be used in health care and education because of its sentience, developing this type of AI brings up ethical concerns. General AI can result in unemployment among humans, as it can do intellectual and creative jobs, mimicking the skills of humans.
OpenAI, the AI research lab behind ChatGPT and DALL-E, is one of the organizations that aim to create general AI that “benefits all of humanity.”
3. Super AI
Super AI definition
Super AI is a hypothetical AI — thankfully — that exceeds human intelligence. It can perform tasks better than humans.
In concept, super AI is an evolved AI that thinks like a human. Like a human being, a super AI also has beliefs, desires, sentiments, and experiences that it understands. It can:
- Solve puzzles
- Make judgments
- Decide on its own
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Maria is an experienced marketing professional in both B2C and B2B spaces. She’s earned certifications in inbound marketing, content marketing, Google Analytics, and PR. Her favorite topics include digital marketing, social media, and AI. When she’s not immersed in digital marketing and writing, she’s running, swimming, biking, or playing with her dogs. -
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