The Stages and Categorizations of AI

- Overview

The modern project to create human-like artificial intelligence (AI) began after World War II, when it was discovered that electronic computers were not only number-crunching machines, but could also manipulate symbols. This can also be achieved without assuming that machine intelligence is the same as human intelligence. 

AI has been named the most widely mentioned technology in recent times, according to a recent study by technology analyst Gartner. Most CIOs agree that AI has the greatest paradigm-shifting power. According to most predictions, AI should occupy the center stage of most human endeavors in the next few decades.

But AI is far from a static technology with a fixed set of principles. In addition to providing the core value of mimicking human intelligence and reasoning to get work done faster and better, AI continues to evolve over time, becoming more capable and richer. This is called weak AI. 

However, the goal pursued by many AI researchers is to develop AI that is in principle the same as human intelligence, called strong AI. Weak AIs are less ambitious than strong AIs and therefore less controversial. However, there are also important controversies associated with weak AI.

- The Categorizations of AI: Capability and Functionality

AI technology creates opportunities to solve real-world problems in health, education, and the environment. In some cases, AI can do things more efficiently and methodically than human intelligence.

There are various ways to create AI, depending on what we want to achieve with it and how we will measure its success. It ranges from extremely rare and complex systems, such as self-driving cars and robotics, to parts of our everyday lives, such as facial recognition, machine translation, and email categorization. The path you choose will depend on what your AI goals are and how well you understand the intricacies and feasibility of various approaches.

AI is classified by many norms. Two of the main categorizations of AI are: capability and functionality. 

AI has three types on the criteria of capability: Artificial Narrow Intelligence (Narrow AI), Artificial General Intelligence (General AI), and Artificial Super Intelligence (Super AI). 

There are four types of AI on the basis of functionality: Reactive Machines, Limited Memory, Theory of Mind, and Self-awareness.

The stages of an AI project can also include: business understanding, data understanding, data preparation, model development, model evaluation, and model operationalization.

- Three Types  of AI - Based on Capabilities

• Artificial Narrow Intelligence (ANI): Also known as weak AI, this is the stage where machines can only perform a limited set of tasks. 
• Artificial General Intelligence (AGI): This is the stage where machines can think and act similarly to humans. 
• Artificial Super Intelligence (ASI): This is the stage where AI systems are more intelligent than humans. 

These are the three stages in which AI can evolve. We have only achieved narrow AI so far. 

As machine learning (ML) capabilities continue to develop and scientists move closer to achieving AGI. Theories and speculation about the future of AI are circulating. ASI is a futuristic idea about the ability of AI to replace human intelligence. For ASI to become a reality, computational programs must surpass human intelligence in all parameters and environments.

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- Four Types of AI - Based on Functionalities

The four primary types of artificial intelligence based on functionality are considered to be reactive machines, limited memory, theory of mind, and self-awareness. 

• Reactive machines: The most basic AI type, only reacting to current situations without storing any memories or past experiences to inform future decisions. 
• Limited memory: Can store a limited amount of information from past experiences to use in decision-making, allowing for some learning and adaptation. 
• Theory of mind: Represents an advanced AI with the ability to understand the thoughts, emotions, and intentions of others, similar to human empathy. 
• Self-awareness: The most advanced theoretical AI type, where a machine would have consciousness and awareness of its own existence and internal states.

The first two types of AI, reactive machines and limited memory, are types that currently exist. Theory of mind and self-aware AI are theoretical types that could be built in the future. As such, there aren't any real world examples yet. 

These four types of AI together enable technologies such as Natural Language Processing (NLP), computer vision, facial recognition, machine learning, and deep learning.  

- AI Capability vs AI Functionality

AI capability refers to an AI's intelligence, while AI functionality refers to its learning approach. 

AI functionality is an output or performance of a system. It is a solution that is complete in itself. When we focus on this definition, it becomes clear: functionality does not accurately describe AI. 

AI capability, on the other hand, is a system’s potential or ability. That includes its potential to solve problems, improve workflows, and increase efficiencies. Now it sounds like we are talking about the solutions to end user problems that LLMs can bring and the new ways of life that AI has enabled in the last decade.