Artificial Intelligence is probably the most complex and astonishing creations of humanity yet.

And that’s disregarding the fact that the field remains largely unexplored, which means that every remarkable AI programs that we see today represents merely the tip of the AI iceberg, as it were. While this fact might have been stated and restated a lot of times, it’s still hard to gain perspective on the potential impact of AI in the future. The reason for this is that the revolutionary impact that AI is getting on society at this relatively early stage in its development.

AI’s rapid expansion and powerful capabilities have made people paranoid about the inevitability and closeness of an AI takeover. Also, the transformation caused by AI in different businesses has made business leaders and the mainstream public think that we are close to achieving the peak of AI research and maxing out AI’s potential. But, understanding the kinds of AI which are possible and the types that exist now provides a clearer image of existing AI capabilities and the long road ahead for AI research.

Knowing the Varieties of AI classification

Considering that AI research purports to create machines mimic human functioning, the level to which an AI system may replicate human capacities is used as the criterion for determining the types of AI. Thus, depending on the way the machine compares to people concerning flexibility and functionality, AI can be categorized under one, among the numerous kinds of AI. Under this method, an AI that can perform more human-like functions with equal levels of proficiency will be considered as a more developed type of AI, whereas an AI that’s restricted functionality and functionality could be considered a more straightforward and less evolved kind.

Based on this standard, there are just two methods by which AI is generally categorized. 1 type is based on classifying AI and AI-enabled machines based on their likeness into the human mind, and also their ability to”believe” and possibly even “feel” such as individuals. According to this system of classification, there are four kinds of AI or AI-based systems: reactive machines, restricted memory machines, the theory of mind, and self-explanatory AI.

1. Reactive Machines

All these are the earliest forms of AI systems which have extremely limited capacity. They emulate the human mind’s capacity. These machines do not have memory-based functionality. This implies such machines cannot use previously obtained experiences to notify their present actions, i.e., those machines do not have the capability to”learn.” These machines may be used for responding to a restricted set or combination of inputs. They can’t be employed to rely on memory to boost their operations based on the same. An example of an AI machine is a system that beat chess Grandmaster Garry Kasparov in 1997, IBM’s Deep Blue.

2. Limited Memory

Restricted memory machines are machines that, along with getting the capacities of purely reactive machines, are capable of learning from historical data to make decisions. Of come under this class of AI. Substantial volumes of training information, train all AI systems, such as the ones using deep learning which they store in their memory for solving issues to form a benchmark model. For example, an image recognition AI is trained with thousands of their labels and pictures to instruct it to name objects it scans. When an image is scanned with this kind of AI, it employs the training pictures as references to comprehend the contents of this image presented to it, and based on its”learning experience” it labels fresh pictures with increasing accuracy.

Almost all present-day AI applications, from chatbots and virtual assistants to self-driving vehicles are all driven by limited memory AI.

3. Theory of Mind

Though the previous two types of AI have been and are present in abundance, the subsequent two types of AI exist, for the time being, either as a theory or a job in progress. Theory of thoughts AI is another level of AI systems which researchers are engaged in innovating. A concept of thoughts level AI is going to have the ability to comprehend the entities it is currently interacting with by emotions, identifying their wants, beliefs, and thought processes. While artificial intelligence is already a budding business and also an area of interest for AI researchers, attaining Theory of mind level of AI will demand development as well. This is because to truly understand human demands, AI machines will have to perceive humans as individuals whose heads can be shaped by numerous factors, essentially”understanding” humans.

4. Self-aware

This is the final stage of AI development, which now exists only hypothetically. Self-aware AI, which, self-explanatory, is an AI which has evolved to be akin to the human brain it has developed self-awareness. Making this kind of Ai, which is decades, if not centuries apart from materializing, is and will be the supreme objective of AI research. This sort of AI will not be able to understand and evoke emotions in those it interacts with, but in addition have feelings, needs, beliefs, and possibly desires of its own. And that is the form of AI that doomsayers of the technology are cautious of. It may also result in catastrophe although the maturation of self-aware can increase our progress by leaps and bounds. This is because, after self-aware, the AI would be capable of having thoughts like self-preservation that might directly or indirectly spell the end to humankind, as such an entity plot elaborate schemes to take over humanity and could outmaneuver the intellect of any person.

The alternative system of classification which is more commonly utilized in tech parlance is that the classification of the tech to Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI).

5. Artificial Narrow Intelligence (ANI)

This kind of artificial intelligence represents all of the existing AI, including even the most complicated and capable AI that’s been created to date. Artificial intelligence describes AI systems that could perform a task autonomously using human-like capabilities. These machines can do nothing more than what they are programmed to do, and so have a narrow or very restricted assortment of competencies. According to the system of classification, these systems correspond to limited memory AI and all the responsive. Even the most complex AI which uses machine learning to teach itself and profound learning drops under ANI.

6. Artificial General Intelligence (AGI)

Artificial General Intelligence is the ability of an AI representative to learn, perceive, understand, and function completely as a human being. These systems will have the ability to independently build numerous competencies and shape generalizations and connections across domains, massively cutting back on time needed for training. By replicating our capabilities that are multi-functional this will make AI systems just as capable as people.

7. Artificial Superintelligence (ASI)

The development of Artificial Superintelligence will probably indicate the pinnacle of AI research, as AGI is becoming by far the most curable forms of intelligence on earth. Besides replicating the multi-faceted intelligence of human beings, ASI will be exceedingly better in everything they do because of greater memory, investigation and faster data processing, and decision-making capabilities. The growth of AGI and ASI can result in a situation most popularly referred to as the singularity. And our existence can threaten as of having such machines at our 12, the potential appears to be attractive or in the least, our way of life.

At this point, it’s not easy to envision the state of our world until more advanced kinds of AI become part of our lives. However, it is clear that there’s a way since the present state of AI development in contrast to where it’s projected to go is in its rudimentary stage to get there. This usually means that now is a little soon to be worrying about the singularity, for anyone holding a negative prognosis for the future of AI, and there’s still time. And for those who are optimistic about the future of AI, the fact that we have merely scratched the surface of AI growth makes the future more exciting.

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