Four levels of Artificial Intelligence (AI) – Achieved and Theoretical

Four levels of Artificial Intelligence

Four levels of Artificial Intelligence (AI) – Achieved and Theoretical

Author – Kaushik Pal


Artificial intelligence (AI) and machine learning (ML) brings a revolution in computer science in the age of Big data. The data is the new fuel for business. And, extracting the insight from this data is the key to business success. In this age of digital transformation, AI and ML are the key technologies to help the organizations understand their data and take proper decision in time.

In this article, we will try to explore different levels of AI and their actual meanings.

What is AI?

In simple term, AI is a combination of processes, algorithms and models to simulate human behaviors like learning, problem solving, responding to input and many more.  Machine learning (ML) and Deep learning (DL) are a part of AI solutions.

What is ML and DL?

Machine learning (ML) is a subset of AI.ML consists of different algorithms and models.  Machine learning algorithms can be classified as supervised learning, unsupervised learning and reinforcement learning.

Deep learning (DL) is again a subset of ML. The purpose of DL is to emulate human neural networks.  DL algorithms are capable of process unstructured data without human assistance.

What are the four levels of AI?

There are four levels of AI (simple to advanced).The first two types are reactive machines and limited memory, which we have achieved. The third and fourth are theory of mind and self-awareness, which are still in theory.

Let us try to understand these fours AIs in details.

Reactive machines – At this level of AI, basic operations based on some input is achieved. In this stage of AI, there is no learning mechanism available. In reactive machine, the AI solution is trained to perform certain tasks and never comes outside that context. It is also not capable to evolve over time, as there is no learning involved. Example of reactive machines are IBM’s Deep Blue chess AI, recommendation engines etc.

Limited memory –   Limited memory AI is capable of storing data and analyze it to improve further. Machine learning comes under limited memory AI. These type of AI solutions can learn over time and improve itself. Examples of limited memory AIs are chatbot, virtual voice service, autonomous vehicles etc.

Theory of mind – This is more advanced and theoretical AI, which we have not achieved yet. In this category, AI will be capable of understanding human thoughts and feelings. It will also interact with human beings in a more meaningful way. This is a two way communication between humans and AI.

Self-awareness – Self-awareness AI is a dream for ultimate AI solutions. In this category, AI will behave like a human being.AI will have human like consciousness, like real world emotions, desires etc. This is a distant dream, yet to achieve.


In this age of digital transformation, AI/MI is an integral part of all solutions.AI and ML can be applied to improve the business efficiency and reduce the cost. We have different forms of AI solutions to help the organizations across business domains. Although, some forms of AI are yet to achieve. Hope, in the coming days, AI will be a part of real human world.


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