One of the biggest technological advancements of the 21st century has to be Artificial Intelligence. It has more impact on our lives than we realize. For the same reasons, there is a huge demand for AI courses and jobs. Today, machines are capable of understanding verbal commands, driving cars, distinguishing pictures, playing games, and doing so many things in a better way than humans can. And the truth is that the AI applications that are commonly used today are just a tip of what AI is capable of. But, whatever applications are there can be categorized into the following types of AI:
This state of AI development only exists hypothetically. Self-aware AI is a type of AI that has evolved to be like the human brain to a point where it has developed self-awareness. However, it will be decades, or even centuries before this type of AI is materialized. This will always be the ultimate objective of AI research. Self-aware AI will be able to comprehend and elicit emotions in people it is interacting with and have desires, needs, beliefs, and emotions of its own. In fact, this is the type of AI that many are wary of. While the development of self-aware AI can boost society’s progress by leaps and bounds, it might also lead to a potential catastrophe. Since this AI is self-aware, they might be capable of ideas like self-preservation which might directly or indirectly end humanity. Doomsayers believe that such a type of AI will be able to outmaneuver the intellect of humans and plot detailed schemes for taking over humanity.
2.Theory of Mind
This one is currently only a concept. This is the next level of AI system that is still a work in progress. Once it is done, it will be able to understand the entities it is interacting with better by discerning their emotions, needs thought processes, and beliefs. Even though artificial emotional intelligence is an area of interest for several top AI researchers and a budding industry, achieving the theory of mind level will require that other branches of AI development as well. The reason for this is that in order to understand the needs of humans, AI will have to perceive humans as someone whose minds are shaped by multiple factors.
These types of machines are ones that have the capabilities of reactive machines, but can also make decisions by learning from historical data. Almost all the existing AI applications that we have today fall under this category. All AI systems of the present day, like the ones that use deep learning, use large volumes of training datasets that are stored in their memory for creating a reference model to solve future problems. For example, to train an image-recognition AI, you will have to use thousands of labelled pictures for teaching it the name of the object it scans. So, when the AI scans a new image, it uses thousands of training images as a reference for understanding the image’s contents. It uses its learning experience for labelling new images accurately. AI applications like virtual assistants, chatbots, and self-driving vehicles are based on this type of AI.
This is the oldest form of AI system that has extremely limited capabilities. They can emulate the ability of the human mind to respond to different types of stimuli. However, they don’t have memory-based functionality which means they can’t inform their present actions by using previously gained experiences. These machines are not capable of learning and can only be used for responding automatically to a limited set of inputs. They can’t improve their operations by relying on memory. An example of this type of AI machine is the Deep Blue by IBM that beat Garry Kasparov, the chess Grandmaster, in 1997.
Apart from the above-mentioned types, there is also an alternate classification system that is used in tech parlance:
1.Artificial Superintelligence (ASI)
This category of AI will mark the pinnacle of all AI research as it will be the most capable form of intelligence on the planet. Apart from replicating human’s multifaceted intelligence, it will be better at everything humans can do because of their faster data analysis and processing, overwhelmingly greater memory, and decision-making capabilities. The AGI and ASI development will lead to the scenario that is referred to as singularity. And while it might seem appealing to have such capable machines at one’s disposal, it might also threaten human’s existence or their way of life.
2.Artificial General Intelligence (AGI)
This classification of AI deals with the AI systems that can learn, understand, perceive, and function as human beings. Such systems will be able to build multiple competencies independently and form generalizations and connections across domains. This will cut down the training time significantly and by replicating the multi-functional capabilities of humans, make AI systems as capable as them.
3.Artificial Narrow Intelligence (ANI)
Artificial Narrow Intelligence or ANI is the representation of all existing AI, even the most capable and complicated ones that have been created to date. It refers to the AI systems that use human-like capabilities for autonomously performing a specific task. However, these machines cannot do anything that they were not programmed to do and have a very narrow or limited range of competencies. As per the aforementioned classification system, this AI system will fall under the reactive machine or limited memory AI. Every AI, even the complex AI that uses deep learning and machine learning for teaching itself, will fall under this category.
According to the International Data Corporation (IDC), by 2024, the AI market will break the $500 billion mark with total revenues reaching $554.3 billion and a CAGR of 17.5%. This growth shows that there is no way of slowing down this progress. However, it is clear that AI is still at a rudimentary stage and it will be years before AI research reaches its pinnacle. When it comes to the negative outlook on AI’s future, it is too soon to be worrying about doomsday and singularity and there is a lot of time to ensure the safety of AI. There is so much the field has to offer in terms of technological advancement as well as employment.