Artificial Intelligence is among the most complex and astonishing technology that humans have yet to develop. It is also ignoring the fact that this field is still largely unexplored. This means that each amazing AI application we have currently is only the end of the AI iceberg in the sense of. Although this is a fact that has been repeatedly reiterated and reaffirmed times, it’s difficult to get a complete view about the possible impact of AI in the coming years. The reason is the profound impact AI has on the world even at an early stage of its development.
The rapid expansion of AI and its powerful capabilities have cause people to worry about the possibility towards the possibility of an AI takeover. Additionally, the change caused by AI across a variety of sectors has led people in the business world and the general public believe that we’re close to reaching the peak level of AI research and maximizing AI’s capabilities. However, understanding the different types of AI that are achievable and the kinds that are available currently will provide a clearer view of current AI capabilities as well as the lengthy journey in the future in AI research.
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Understanding the various types of AI classification
Because AI research designe to help machines replicate human capabilities The degree to the extent that an AI machine can mimic human abilities is the basis for determining the kinds of AI. Therefore, based on the way a machine performs against humans with regard to capability and efficiency, AI can be classified as one of the many kinds of AI. In this system an AI that is able to perform more human-like tasks with similar levels of proficiency is consider to be an upgraded kind of AI, whereas an AI with only a few functions and capabilities would be considered to be a less complex and less developed kind.
Based on this criteria, there are two ways AI is typically classified. One is based on categorizing AI and AI-enabled devices based on their resemblance to human mind, as well as their capacity to “think” and perhaps even “feel” like humans. Based on this method of classification there are four types of AI or AI-based systems: reactive machines limited memory machines, theories of mind and autonomous AI.
1. Reactive Machines
These are the most basic kinds of AI systems, which have a limited capabilities. They mimic the human brain’s ability to react to various types of stimuli. However, they do not possess the ability to use memory for their functions. They are unable to use previous experiences to guide their current decisions, i.e., these machines don’t have the capability to “learn.” These machines are only capable of automating the response to a certain number of inputs or combinations. They are not able to make use of memory to enhance their performance based on the same. An example of an active AI device includes IBM’s Deep Blue, a machine that defeated chess Grandmaster Garry Kasparov in 1997.
2. Limited Memory
Machines with limited memory are those that are, in addition to possessing the abilities of pure reacting machines, are equippe to learn from previous information to make choices. The majority of the applications are known to us fall into this class of AI. The majority of current AI systems, including those that employ deep learning are traine by huge amounts of training data which they keep in their memory, forming the basis for solving future challenges. For example an image recognition AI is trained by using thousands of images and their labels in order to train it to recognize things it scans. If an image gets processed by an AI it makes use of the images it trained on as references to learn what the images’ contents are that is shown to it and, based on its “learning experience” it labels new images with greater accuracy.
The majority of current AI applications including chatbots and virtual assistants, to self-driving cars are driven by a limited memory AI.
3. Theory of Mind
While the two prior kinds of AI have been abundantly present The next two kinds of AI are in the beginning or as an idea or as a research project in development. Theory of Mind AI will be the next stage of AI systems which researchers are currently in the process of developing. The theory of mind level AI can expecte more effectively understand the people that it interacts with by understanding their desires, emotions, opinions, and thinking processes.
Although Artificial Emotional Intelligence is developing and is an area of study for top AI researchers, getting to the Theory of Mind level AI will require further development across other fields of AI as well. In order to fully be able to comprehend the human condition, AI machines must be able to see humans as beings whose minds are shaped by a variety of elements, ultimately “understanding” humans.
4. Self-aware
This is the last phase of AI development , which is currently only in a hypothetical way. Self-aware AI self-explanatory can describe as an artificial intelligence that’s developed to be so similar to human brains that it has evolved self-awareness. Making this kind of Ai that is several decades, if perhaps decades away from becoming reality will forever be the primary goal in the entire field of AI research.
The type of AI that is developed is not just capable of recognizing and stimulating emotions from those who it comes into contact with. It will it will also possess needs, emotions as well as beliefs and needs of its own. This is the kind of AI that the doomsayers of technology are skeptical of. While the advancement of self-aware AI could help us advance as a society by leaps and bounds it could also lead to disaster. The reason is that once it becomes self-aware, the AI could be able to develop thoughts like self-preservation that could directly or indirectly lead to the end of humanity because such a thing could easily beat the brain that any person has, and create elaborate plans to conquer humanity.
The alternative system of classification which is more widely use in tech parlance is to classify technologies according to Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI) as well as Artificial Superintelligence (ASI).
5. Artificial Narrow Intelligence (ANI)
AI is the basis for all current AI that exist, including the most complex and powerful AI that has develope up to now. Artificial narrow intelligence is AI systems that are able to complete a task by using human-like abilities. These machines are unable to do anything other than what they’re programme to do and therefore have a limited or restricted spectrum of abilities. According to the above classification system they are all adaptive and limited memory AI. Even the most complicated AI which uses deep learning and machine learning to help itself learn falls within ANI.
6. Artificial General Intelligence (AGI)
Artificial General Intelligence refers to the capacity for AI AI agent to be able to learn and comprehend, sense and perform in a way that is similar to humans. AI systems can independently develop multiple skills and establish relationships and generalisations between domains, dramatically cutting down the amount of time needed to learn. This can allow AI systems as efficient as human beings, replicating the multi-functional abilities of humans.
7. Artificial Superintelligence (ASI)
The advancement of Artificial Superintelligence will probably mark the top in AI research, since AGI will be by far the most efficient kinds of intelligence in the world. ASI as well as replicating the multi-faceted human intelligence and being remarkably more efficient in everything they do due to larger memory, more efficient data processing and analysis and the ability to make decisions. The growth of AGI and ASI could lead to an outcome that is often known as the singularity. While the possibility of having these powerful devices at our disposal is attractive. These machines could be a threat to our existence, or, at the very minimum the way we live.
