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| Artificial Intelligence |
7 Types Of Artificial Intelligence
Artificial intelligence is one of humanity's most complicated and impressive creations. That's not even taking into account the fact that the topic is still substantially untapped, which implies that any spectacular AI application we see today is only the tip of the AI iceberg. While this fact has been mentioned and reiterated several times, it is still difficult to acquire a full view on the future influence of AI. This is due to AI's revolutionary influence on society, especially at such an early stage in its progress.
People are fearful of an AI takeover due to AI's rapid growth and powerful capabilities. Furthermore, the transformation brought about by AI in various industries has led business leaders and the general public to believe that we are on the verge of reaching the pinnacle of AI research and fully realizing AI's potential. Understanding the types of AI that are possible and those that exist now, on the other hand, will provide a more complete picture of existing AI capabilities and the long road ahead for AI research.
Understanding AI categorization types
Because AI research aims to make robots mimic human-like functioning, the degree to which an AI system can reproduce human skills is used to classify AI. Thus, AI may be categorised as one of several categories based on how a machine compares to humans in terms of variety and performance. In such a system, an AI that can execute more human-like functions with equal levels of competency is deemed more advanced, whereas an AI with restricted functionality and performance is considered simpler and less evolved.
There are two approaches to classify AI based on this criterion. One classification is based on AI and AI-enabled robots' resemblance to the human mind and their ability to "think" and maybe "feel" like humans. This categorization method divides AI or AI-based systems into four categories: reactive machines, limited memory machines, theory of mind, and self-aware AI.
TYPES OF AI (ARTIFICIAL INTELLIGENCE)
1. Machines That Respond
These are the most primitive kind of AI systems, with extremely restricted capabilities. They simulate the ability of the human mind to respond to many types of stimuli. These devices lack memory-based capabilities. This means that such robots cannot utilize prior experiences to guide their current behavior, i.e., they lack the ability to "learn." These devices could only be utilized to respond to a restricted set or combination of inputs automatically. They cannot rely on memory to boost their operations. IBM's Deep Blue, which beat chess Grandmaster Garry Kasparov in 1997, is a notable example of a reactive AI computer.
2. Memory Impairment
Limited memory machines are machines that, in addition to being completely reactive, may learn from previous data to make judgments. This category of AI encompasses nearly all present applications that we are aware of. All modern AI systems, including those that use deep learning, are taught using massive amounts of training data, which they store in memory to construct a reference model for addressing future issues. For example, an image recognition AI is taught to name things it scans using hundreds of images and their labels When such an AI scans an image, it utilizes the training photos as references to comprehend the contents of the image supplied to it, and then classifies fresh images with increasing accuracy based on its "learning experience."
Almost all AI applications today, from chatbots and virtual assistants to self-driving cars, are powered by limited memory AI.
3. Mind-Body Theory
While the preceding two categories of AI have been and continue to be abundant, the next two types of AI exist just as an idea or as a work in progress for the time being. Mental theory AI is the next level of artificial intelligence systems that researchers are actively developing. A theory of mind AI will be able to better comprehend the creatures with whom it interacts by determining their needs, emotions, beliefs, and mental processes. While artificial emotional intelligence is now a burgeoning business and a focus for prominent AI researchers, obtaining Theory of mind level AI would necessitate advancements in other areas of AI as well. This is due to the fact that, in order to properly grasp human wants, AI computers must recognize humans as individuals whose brains may be molded by a variety of variables, basically "knowing" humans.
4. Self-awareness
This is the last step of AI development, which exists only in theory at the moment. Self-aware AI is an AI that has grown to be so similar to the human brain that it has gained self-awareness. Developing this form of AI, which is decades, if not centuries, away, is and will always be the ultimate goal of all AI research. This sort of AI will not only comprehend and elicit emotions in individuals with whom it interacts, but will also have emotions, wants, beliefs, and maybe desires of its own. This is the kind of AI that technology skeptics are concerned about. Although the emergence of self-awareness has the potential to accelerate our growth as a civilization, it also has the potential to be disastrous. This is because, once self-aware, AI would be capable of possessing thoughts like self-preservation, which might either directly or indirectly mark the end of mankind, since such an entity could easily outmaneuver any human being's intellect and create sophisticated plots to take over humanity.
The alternative way of classification, which is more often used in tech jargon, divides technology into Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI) (ASI).
5. Artificial Narrow Intelligence (ANI) (ANI)
This form of artificial intelligence encompasses all extant AI, including the most complex and competent AI yet devised. Artificial narrow intelligence refers to AI systems that can only do a single job independently while retaining human-like characteristics. Because these robots can only perform what they are trained to do, they have a very limited or narrow range of competences. These systems relate to all reactive and limited memory AI, according to the previously specified categorization scheme. ANI encompasses even the most advanced AI, which combines machine learning and deep learning to train itself.
6. General Intelligence Artificial (AGI)
The capacity of an AI agent to learn, sense, understand, and act entirely like a human being is referred to as Artificial General Intelligence. These systems will be able to build various competences on their own and make linkages and generalizations across domains, significantly reducing training time. By mimicking our multifunctional capacities, AI systems will be as competent as humans.
7. AI (Artificial Intelligence) (ASI)
The creation of Artificial Superintelligence (AGI) will most likely be the apex of AI research, as AGI will be by far the most competent forms of intelligence on the planet. ASI, in addition to mimicking human intellect, will be much superior at all they do due to vastly increased memory, quicker data processing and analysis, and decision-making skills. The emergence of AGI and ASI will result in a scenario known as the singularity. While the prospect of having such powerful tools at our disposal is tempting, these devices may potentially endanger our survival, or at the very least our way of life.
At this time, it is difficult to imagine what our world will be like when more powerful varieties of AI become available. However, it is evident that there is still a long way to go because the current status of AI development in comparison to where it is anticipated to go is still in its early stages. For those who have a pessimistic view of AI's future, this suggests that it's a bit early to be concerned about the singularity, and there's still time to secure AI safety. And for those who are bullish on AI's future, the fact that we've only scratched the surface of AI research makes the future even more fascinating.
