Artificial intelligence is a science, and like all examples it has its subdivisions. Look down, what are the types of artificial intelligence according to their capabilities and functionalities within the spectrum of approximation between the operation of machines and the human brain.
Artificial intelligence and its types
Since AI research aims to make machines “emulate” human-like functioning, the degree to which an AI system can replicate human capabilities is used as a yardstick for determining which types exist.
Depending on how a machine compares to humans in terms of versatility and performance, artificial intelligence can be classified into one or more types of AI.
The greater the ability to perform more human-like functions with equivalent levels of competence, the more evolved type of artificial intelligence will be considered, while those with limited functionality and performance will be considered a simpler and less evolved type.
1. Reactive machines
These are the oldest forms of AI systems with limited capacity. They mimic the ability of the human mind to respond to different types of stimuli. The machines do not have memory-based functionality.
In short, it means that they cannot use previously acquired experiences to inform their present actions, that is, these machines do not have the ability to “learn.” Its usability comes down to automatically responding to a limited set or combination of inputs. His classic example is Deep blue from IBM that beat Garry kasparov in a chess duel.
2. Limited memory
The machines with limited memory are those that, in addition to having the resources of purely reactive machines, are also capable of learning from historical data to make decisions. Almost all existing applications that we know of belong to this category of artificial intelligence.
All current systems, such as those that use deep learning , are trained by large volumes of training data that are stored in their memory to form a reference model for solving future problems. From chatbots and virtual assistants for autonomous vehicles, all powered by limited memory artificial intelligence.
3. Theory of mind
For now, it works as a concept or a work in progress. Mind-based artificial intelligence theory is the next level of artificial intelligence systems that researchers are committed to innovating.
A theory at a mental level will be able to better understand the beings with whom it interacts, discerning their needs, emotions, beliefs and thought processes.
While artificial emotional intelligence is already a developing industry and an area of interest for leading computer science researchers, reaching this level will also require the development of other branches of artificial intelligence.
To truly understand human needs, artificial intelligence machines will have to perceive humans as individuals whose minds can be shaped by many factors, in fact “understanding” humans.
If theory of mind is a work-in-progress concept, self-aware AI is a hypothetical formulation. Not only will this type of AI be able to understand and evoke emotions in those with whom it interacts, it will also have emotions, needs, beliefs, and potentially desires of its own.
It’s the kind of artificial intelligence that tech pessimists are wary of. While the development of self-awareness could boost our progress as a civilization by leaps and bounds, it could also lead to catastrophe: the movie “The Matrix” and the domination of machines.
Once self-aware, AI could come up with ideas such as self-preservation, which could directly or indirectly spell the end of humanity, as such an entity could easily overwhelm the intellect of any human being and hatch elaborate plans to domesticate. or enslave humanity.
Technical and functional classifications
5. Narrow Artificial Intelligence (ANI)
This type of artificial intelligence represents all existing AI, including the most complicated and capable AI ever created. ANI refers to artificial intelligence systems that can only perform a specific task autonomously, using human-like resources.
These machines cannot do anything other than what they are programmed to do and therefore have a very limited or narrow range of competencies. Even the most complex AI you use machine learning Y deep learning the teaching itself is framed in the ANI.
6. General artificial intelligence (AGI)
General artificial intelligence is the ability of the artificial intelligence agent to learn, perceive, understand and function fully as a human being. These systems will be able to independently build multiple competencies and form connections and generalizations between domains, greatly reducing the time required for training.
This will make artificial intelligence systems as capable as humans in replicating our cross-functional capabilities.
7. Artificial superintelligence (ASI)
From what we can imagine, it would be the limit of AI development. The development of artificial superintelligence will likely mark the pinnacle of AI research, as AGI will become by far the most capable form of intelligence on the planet.
ASI, in addition to replicating the multifaceted intelligence of humans, will be extremely better at everything it does due to overwhelmingly larger memory, faster data processing and analysis, and decision-making capabilities.
The development of AGI and ASI will lead to a scenario known as singularity. And while the potential of having such powerful machines at our disposal seems attractive, these machines can also threaten our existence, or at least our way of life.
These are the 7 classifications designed to determine the level of an artificial intelligence, if we think about capacity, we are in the middle and evolving, but when we take into account the technical classification, we are in the first of the 3 stages and it will be take some time to (and if) reach the following.