1. Based on Capability
- Narrow AI (Weak AI): AI systems that are designed and trained for a specific task, such as facial recognition, language translation, or playing chess. These systems operate under a limited set of constraints and do not possess general intelligence. Examples include Siri, Alexa, and IBM’s Watson.
- General AI (Strong AI): A theoretical form of AI that would have the ability to learn, understand, and apply intelligence across a wide range of tasks, much like a human being. General AI does not yet exist and remains a goal for future development.
- Superintelligent AI: A hypothetical AI that surpasses human intelligence across all aspects, including creativity, decision-making, and emotional intelligence. This type is purely speculative at this point and often discussed in the context of ethical considerations and long-term AI safety.
2. Based on Functionality
- Reactive Machines: The most basic type of AI that can only react to current situations without any memory or understanding of the past. An example is IBM’s Deep Blue, which played chess without learning from previous games.
- Limited Memory: AI systems that can use past experiences or data to make decisions, albeit temporarily. Most modern AI applications, like self-driving cars, fall into this category as they use historical data to make real-time decisions.
- Theory of Mind: This type of AI is in the conceptual stage and aims to understand human emotions, beliefs, and thoughts, and interact socially. Theory of Mind AI is not yet realized but is an area of active research.
- Self-Aware AI: The most advanced form of AI, which would have its own consciousness, self-awareness, and emotions. This type does not currently exist and is largely a subject of science fiction and philosophical debate.
3. Based on Learning Techniques
AI comes in many forms. And while the general process of automated technology carrying out a series of tasks remains consistent, how and why this happens will vary. Here are some examples of different types of AI which you might come across.
Deep Learning
An evolution of machine learning, this more thorough approach sees AI programmed in such a way that they’re able to identify images, sounds, and text without the need for human input. While with machine learning you may have to physically describe an image to AI, with deep learning they will be able to process and understand it themselves.
Natural Language Processing (NLP)
If you’ve ever spoken to Siri, Alexa, or any other virtual assistant, you will have interacted with NLP. This technology is able to comprehend, manipulate, and generate human language in a way that allows it to have its very own “voice”. NLP can understand questions you give it, then respond accordingly. It can also be used in text form, such as a chatbot on a website.
Computer vision
This futuristic form of tech allows computers to interpret and analyze the human world through the classification of images and objects. In doing so, it allows an AI to see the world through the eyes of a living person. This kind of technology is most commonly associated with driverless cars, where the vehicle needs to be able to process the world around it as a normal driver would.
Machine Learning
This AI approach sees a series of data and algorithms run to formulate a picture of how a human would approach a situation or task. Over time, the program is able to adapt and even learn more about the human thinking process, which helps it to improve its overall accuracy.
Generative AI
A popular online fad in 2023, generative AI is the name given to technology which is able to create images, text, or other media independently. A user simply needs to input what they want created, with the AI able to draw on their input training to produce something that has similar characteristics.
Speech recognition
One of the oldest forms of AI, this tech is able to understand and interpret what you’re saying out loud, then convert it into text or audio format. This kind of technology is often confused with voice recognition – which instead of transcribing what you’re saying, will instead only be able to recognise the voice of the user.
Robotic Process Automation (RPA)
RPA technology is a software which makes it easier to build, deploy, and manage robots that emulate human interactions. The robotic helpers are able to carry out a number of tasks virtually, at speeds which humans would be incapable of replicating.
AI comes in many forms. And while the general process of automated technology carrying out a series of tasks remains consistent, how and why this happens will vary. Here are some examples of different types of AI which you might come across.
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