The Many Faces of Artificial Intelligence

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Dinesh Elumalai explains the various species of artificial intelligence and how these affect human existence in an increasingly uncertain world

Most likely one of humanity‘s most complex and amazing inventions to date is artificial intelligence. And that ignores the fact that the field is still largely unexplored, which means that every incredible AI application we currently see only scratches the surface of the field. Even though this fact has been stated and reiterated numerous times, it is still difficult to fully understand the potential future impact of AI. This is because, even at this early stage in its development, AI is having a revolutionary impact on society.

People are paranoid about an impending AI takeover due to the technology‘s explosive growth and potent capabilities. Additionally, business leaders and the general public now believe that AI research has reached its pinnacle and that AI’s potential has been fully realized as a result of the transformation that AI has brought across various industries. The long road ahead for AI research will become clearer with a better understanding of the types of AI that are currently possible and those that already exist.

The degree to which an AI system can mimic human capabilities is used as the criterion for categorizing the different types of AI because AI research aims to make machines mimic human-like functioning. Thus, among the various types of AI, a machine can be categorized under one of them depending on how versatile and effective it is compared to humans. A more advanced type of AI will be one that can perform more tasks that are similar to those performed by humans with an equivalent level of skill, while a less complex and less evolved type of AI will be one that has more limited functionality and performance.

While there are many different ways to categorize artificial intelligence, the two main classifications are based on the capabilities and the functionalities of the technology.

All currently existing artificial intelligence, including the most sophisticated and powerful AI ever developed, falls under this category. Artificial narrow intelligence is used to describe AI systems that can only carry out a single task on their own while possessing human-like abilities. These machines have a very small or restricted set of competencies because they are only capable of performing the tasks for which they have been programmed. These systems correspond to all reactive and limited memory AI, in accordance with the classification scheme mentioned above. Even the most advanced AI that learns new things through deep learning and machine learning is included in ANI.

The stage of artificial intelligence development at which machines will be able to think and act similarly to how we do as humans is known as AGI, also known as strong AI.

Although strong AI has yet to be demonstrated, it is expected that we will soon be able to build machines that are as intelligent as humans.

The ability of an AI agent to think, perceive, comprehend, and act exactly like a human being is referred to as artificial general intelligence. These systems will be able to develop multiple competencies on their own, make connections between domains, and draw generalizations, significantly reducing training time. This will allow AI systems to mimic our ability to multitask, making them as capable as humans.

Artificial super intelligence is the stage of artificial intelligence where computers will be smarter than people. Currently, ASI is an imagined scenario from science fiction movies and books where machines have taken over the world.

If we take into account our current rate of advancement, I think that machines won’t be too far from reaching this stage.

The state of our world when more complex types of AI exist now is difficult to imagine.

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Yves Mulkers

Yves Mulkers is the founder of 7wData and a widely followed voice in the data and AI community. He curates the 7wData and AI Beat newsletters, reaching hundreds of thousands of data and AI professionals, and writes on data strategy, analytics, AI, and the evolving data ecosystem.