4 Types of Artificial intelligence:
1. Reactive Machines
These are the oldest forms of AI(Artificial intelligence) systems that have extremely limited capacity. They emulate the human mind’s ability to respond to different kinds of stimuli. These machines do not have memory-based functionality. This means such machines cannot use previously gained experiences to inform their present actions, i.e., these machines cannot “learn.” These machines could only be used for automatically responding to a limited set or combination of inputs. They cannot be used to rely on memory to improve their operations based on the same. A familiar instance of a reactive AI machine is IBM’s Deep Blue, a robot that defeated chess Grandmaster Garry Kasparov in 1997.
2. Limited Memory
Limited memory machines are machines that, in enhancement to having the abilities of genuinely reactive machines, are also competent in learning from historical data to make choices. Nearly current applications that we know of come under this section of AI. All present-day AI systems, such as those using deep learning, are guided by large bulks of training data that they save in their memory to develop a source model for determining future problems.
For instance, an image identifying AI is prepared using thousands of images and their labels to teach it to name things it considers. When an image is scanned by such an AI, it uses the training pictures as references to learn the contents of the picture conferred to it, and based on its “learning experience” it labels new pictures with enhancing accuracy.
3. Theory of Mind
While the earlier two models of AI have been and are seen in abundance, the next two types of AI exist, for now, either as a theory or a work in progress. Theory of mind AI is the subsequent level of AI methods that researchers are currently involved in innovating. Theory of mind level AI will be capable to better understand the objects it is associating with by determining their requirements, emotions, feelings, and thought processes.
While artificial emotional intelligence is now a growing industry and an area of interest for managing AI researchers, producing the Theory of mind level of AI will need improvement in other parts of AI as well. This is because to understand human needs, AI machines will have to observe humans as individuals whose brains can be formed by multiple portions, actually “understanding” humans.
This is the final stage of AI evolution which currently survives only hypothetically. Self-aware AI, which, self explanatorily, is an AI that has emerged to be similar to the human mind that it has amplified self-awareness. Creating this kind of Ai, which is decades, if not centuries away from developing, is and will always be the ultimate objective of all AI analysis. This type of AI will not only be able to experience and elicit emotions in those it associates with, but also have emotions, requirements, beliefs, and probably wishes of its own. And this is the type of AI that doomsayers of the technology are cautious of.
Although the development of self-aware can potentially boost our progress as a civilization by leaps and bounds, it can also potentially lead to catastrophe. This is because once self-aware, the AI would be capable of having ideas like self-preservation which may directly or indirectly spell the end for humanity, as such an entity could easily exceed the ability of any human being and plot elaborate schemes to take over humanity.
The alternate system of classification that is more generally used in tech parlance is the classification of the technology into Artificial Narrow Intelligence (ANI), Artificial General Intelligence (AGI), and Artificial Superintelligence (ASI).