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.
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
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.
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 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.
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.
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!
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