It’s safe to say that artificial intelligence (AI) is one of humankind’s most sophisticated and fascinating inventions yet. Furthermore, the topic is still extensively untapped, which implies that any wonderful AI application that we see today is just the tip of the AI iceberg. As often as it has been said, it is difficult to get a clear picture of the future implications of artificial intelligence (AI). The reason for this is that AI is having a revolutionary effect on society even at this early stage of its development.
In light of AI’s rapid development and tremendous powers, many people have become concerned about an AI takeover. Because of this, corporate executives and the general public believe that AI research and its promise are nearing its peak and are close to being fully realized. The forms of AI that are achievable and the types that are already in use will give a clearer sense of the current AI capabilities and the long road ahead in AI research.
4 types of Artificial Intelligence
The degree to which an AI system can mimic human capabilities is used as a criterion for distinguishing the types of AI because AI research claims to make computers emulate human-like functioning. As a result, a machine’s adaptability and performance can be compared to that of a human to determine which sort of AI it falls under. A more advanced sort of AI would be one that can execute human-like functions with a similar level of competency, whereas a less advanced type of AI would be one that is simpler and less evolved.
AI can be divided into two categories using this criterion. The ability to “think” and “feel” like humans is one way to categorize artificial intelligence (AI) and AI-enabled machines. Reactive machines, restricted memory machines, theory of mind, and self-aware AI are all included in this classification system.
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Type 1. Reactive Machines
Limited in capabilities, these are the earliest AI systems. They mimic the brain’s ability to react to various inputs. Memory-based functionality is not available on any of these computers. Because these robots lack the ability to “learn,” they are unable to use their past experiences to guide their current actions. Only a limited number of inputs or combinations of inputs could be used to control these machines. They are unable to utilize memory to enhance their activities in the same way as computers do. IBM’s Deep Blue, which defeated chess Grandmaster Garry Kasparov in 1997, is a popular example of a reactive AI machine.
Type 2. Limited Memory
It is possible for limited memory machines to make judgments based on past data in addition to their usual reactive capabilities. This area of artificial intelligence encompasses the vast majority of currently developed applications. Deep learning systems, for example, are trained using enormous amounts of training data that they retain in their memory as a reference model for solving future problems. For example, an image recognition AI is taught to name items it scans using hundreds of photos and their labels. A computerized system that scans photographs uses the training images as a guide to figure out what’s going on in the image in front of it, and then it improves its accuracy as it gains more “learning experience.”
Virtual assistants, chatbots, and self-driving cars are all examples of modern AI applications that rely on low memory AI.
Type 3. Theory of Mind
While the first two categories of artificial intelligence have already been developed and can be found in plenty, the third and fourth types of artificial intelligence are only concepts or ongoing projects at this time. Researchers are now working on the next generation of AI systems, known as theory of mind AI. A theory of mind level AI will be able to discern the wants, emotions, beliefs, and mental processes of the beings it is dealing with. In order to get to Theory of mind level of AI, it will be necessary to progress in other fields as well, including artificial emotional intelligence, which is already a budding industry and an area of interest for major AI researchers. The reason for this is that in order for AI computers to genuinely comprehend human wants, they must consider humans to be unique individuals whose thoughts are influenced by several circumstances.
Type 4. Self-aware
For the time being, artificial intelligence can only be imagined at this point. Artificial Intelligence (AI) that has gained self-awareness is known as self-aware AI, or simply AI that is self-aware. The ultimate goal of all AI research is to create this form of AI, which is decades, if not centuries, away from becoming a reality. In addition to being able to understand and elicit emotions from those it interacts with, this sort of AI will have its own feelings, wants, beliefs, and maybe goals. There are others that are concerned about this form of AI. A self-aware civilization could lead to great advances, but it also has the ability to bring about disasters. Due to its ability to outmaneuver human intelligence and devise sophisticated plots to take over humanity once it becomes self-aware, AIs may one day have ideals like self-preservation, which might mark the end of humanity as we know it.
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Other types of AI
Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI) are the types of artificial intelligence (AI) that are more commonly utilized classification systems in the IT world.
Artificial Narrow Intelligence (ANI)
Even the most complex and capable artificial intelligence can be represented by this form of artificial intelligence. Those AI systems that can only carry out a single task on their own, with human-like capabilities, are known as artificial narrow intelligence (AINI). These machines can only accomplish what they have been designed to do, and as a result, their skill set is somewhat limited. They are all reactive and limited-memory AI systems according to this classification method. AI that uses machine learning and deep learning to learn falls under the umbrella of ANI, even the most complicated AI.
A computer program that can think for itself (AGI)
The ability of an AI agent to learn, sense, understand, and act like a human being is known as Artificial General Intelligence (AGI). Systems like this one will be able to teach themselves several skills at the same time, reducing the amount of time it takes to train new employees by a huge margin. As a result, AI systems will be able to perform at the same level as humans.
Artificial Super Intelligence (ASI)
For AI research to reach its zenith, it is likely that AGI will be the most powerful kind of intelligence ever created. ASI will not only be able to replicate the human brain’s many facets of intelligence, but they will also be far more efficient in their data processing, analysis, and decision-making. AI and ASI advancements will lead to a scenario known as the singularity. Having such powerful technologies at our disposal may sound enticing, but they could endanger our very survival or at the very least our way of life, depending on how they are used.
It’s impossible to imagine what our world will look like when we have more powerful forms of artificial intelligence. While this may sound like a lofty goal, it’s apparent that AI development is still in its infancy compared to where it’s expected to go. This suggests that individuals who have a pessimistic view of AI’s future should not worry about the singularity just yet, as there is still time to protect AI. People who are positive about the future of artificial intelligence will find it even more exhilarating to realize that we have only just begun to scrape the surface of AI development.
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