The Differences in AI Capabilities Explained

AI is a rather large concept that encompasses many areas in up-and-coming technology and production. In our last blog, we defined Artificial Intelligence (AI) and gave the basics of how it works. We also discussed the differences between strong and weak AI and touched base on pop culture’s depictions versus how it is used in industry. 

Sci-fi depiction of AI
Sci-fi depiction of AI

Different Capabilities of AI

Because of these differences in understanding in a field that is so large, AI can be compartmentalized into four stages of capability: 

  • Reactive Machines 
  • Limited Memory 
  • Theory of Mind 
  • & Self Awareness 

Reactive Machines 

This is the most practical AI capability and is used in modern problem-solving. Reactive machines have no memory, are task-specific, and are considered weak AI. They can make predictions based on identified components but cannot draw on past memory or experience in decision-making. They can only rely on the code that has been provided to them. 

Limited Memory. 

This capability has a small amount of memory, hence the name. Limited Memory programs can use some past decisions to inform future ones. It is currently being used in the programming of self-driving cars like Tesla. 

Theory of Mind 

As of today, this is where things start to verge on science fiction. These theoretical programs or machines have the social intelligence to understand emotions and therefore can predict human behavior. They also would be able to predict the behaviors of similar programs. 


Finally, we have self-awareness. As the name implies, these theoretical machines can obtain consciousness allowing them to understand their place in the world and that they are, in fact, AI. This is the closest concept to the literal replication of the human brain.  

Augmented Intelligence vs. Artificial Intelligence 

The differences in Artificial Intelligence do not stop at its applications. The name Artificial intelligence itself is a matter of debate in the technological industries. Many have now begun using the term Augmented Intelligence. This name switch is because some believe that the public’s understanding of the term Artificial Intelligence is too much like that of Sci-Fi pop culture which creates false expectations. And with these false expectations follows disappointment. Even in the face of revolutionary advancements. 

Using the term, Augmented Intelligence, provides a neutral connotation, lowering expectations. It makes AI sound more realistic in terms of its weak capabilities as it will simply improve products rather than innovate or dominate them. 

Additionally, the same people who use the phrase Augmented Intelligence delegate the name of Artificial Intelligence to what is known as “True AI” or Artificial General Intelligence (AGI). True AI is associated with the technological singularity, the point in technological achievement where the human mind can be downloaded/replicated. This possibility can theoretically lead to a future ruled by artificial superintelligence that surpasses human cognitive abilities. Believers are convinced that the road to AGI consists of cognitive and quantum computing.  

Quantum Computing 

Quantum Computing involves an understanding of quantum mechanics, the study of subatomic particles. It uses collective properties from quantum states to make calculations on a subatomic level that regular computers cannot. With this type of software, a machine would be able to make calculations and decisions in real time just as fast, if not faster, than the human brain. 

Cognitive Computing 

Sometimes used interchangeably with AI but varying slightly, Cognitive Computing replicates and alters human thought processes with computerized models. Cognitive computing is interactive, adaptive, contextual, and collaborative. It can gather information from a variety of sources including forming and asking questions if some information is missing or something is unclear. 

Cognitive Computing vs. AI

So, what is the difference between Artificial Intelligence and cognitive computing? Think of thumbs versus fingers.

AI is an umbrella term for all technology that attempts to replicate a certain function of the human brain. It is used to describe algorithms that allow technology to make decisions based on information provided or collected. 

Cognitive Computing, on the other hand, is different in that it solely attempts to replicate human thought in real time. Therefore, cognitive computing is a form of AI, but not all AI obtains cognitive computing.

IBM’s Watson is the most prevalent example of Cognitive computing currently. 

IBM's Watson Super-computer
IBM’s Watson Super-computer

AI uses Cognitive computing in applications like robotics, virtual reality, expert systems, and neural networks which will be explained in our next installment.

Thank you for reading! In our next blog, we will cover Machine Learning, Neural Networks, and Deep Learning… Oh My! 


In conclusion, the AVT Simulation Training Center’s exploration of AI capabilities highlights the nuanced spectrum of artificial intelligence, from practical reactive machines to the theoretical realms of self-awareness and the conceptual differences between augmented and artificial intelligence. This nuanced exploration underscores the importance of understanding AI’s varying capabilities and its implications for future technological advancements. Emphasizing terms like “Augmented Intelligence” helps recalibrate expectations, aligning public perception with the realistic progression of AI technologies. Through this, the article contributes to a more informed discourse on AI’s role in shaping our technological landscape.

Key Points:

  • Distinction between reactive machines, limited memory, theory of mind, and self-awareness stages in AI.
  • Debate over “Artificial Intelligence” vs. “Augmented Intelligence” terminology to manage expectations.
  • Discussion on the potential of quantum and cognitive computing in achieving true AI or AGI.
  • The importance of distinguishing between AI and cognitive computing, with examples like IBM’s Watson.


  • AI Capabilities
  • Reactive Machines
  • Limited Memory
  • Theory of Mind
  • Self-Awareness
  • Augmented Intelligence
  • Artificial General Intelligence (AGI)
  • Quantum Computing
  • Cognitive Computing

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