Types of A.I-

AI is broadly categorized into two types:

Capability-Based Types of Artificial Intelligence

Based on how they learn and how far they can apply their knowledge, all AI can be broken down into three capability types: Narrow AI, general AI and super AI. Here’s what to know about each.

• Narrow AI:?AI designed to complete very specific actions; unable to independently learn.ANI technologies are built to serve and excel in one cognitive capability, and cannot independently learn skills beyond its design. They often utilize machine learning and neural network algorithms to complete these specified tasks. For instance, natural language processing is a type of narrow AI because it can recognize and respond to voice commands, but cannot perform other tasks beyond that.?
• Artificial General Intelligence:?AI designed to learn, think and perform at similar levels to humans .The goal of designing artificial general intelligence is to be able to create machines that are capable of performing multifunctional tasks and act as lifelike, equally-intelligent assistants to humans in everyday life.?

Though still a work in progress, the groundwork of artificial general intelligence could be built from technologies such as supercomputers, quantum hardware and generative AI models like ChatGPT.?

• Artificial Superintelligence:?AI able to surpass the knowledge and capabilities of humans. It’s theorized that once AI has reached the general intelligence level, it will soon learn at such a fast rate that its knowledge and capabilities will become stronger than that even of humankind.?

ASI would act as the backbone technology of completely self-aware AI and other individualistic robots. Its concept is also what fuels the popular media trope of “AI takeovers.” But at this point, it’s all speculation.

2.Functionality-Based Types of Artificial Intelligence

Functionality concerns how an AI applies its learning capabilities to process data, respond to stimuli and interact with its environment. As such, AI can be sorted by four functionality types.

• Reactive Machine AI:?AI capable?of responding to external stimuli in real time; unable to build memory or store information for future.. Additionally, reactive machines can only respond to a limited combination of inputs. Reactive machines are the most fundamental type of AI.

In practice, reactive machines are useful for performing basic autonomous functions, such as filtering spam from your email inbox or recommending items based on your shopping history. But beyond that, reactive AI can’t build upon previous knowledge or perform more complex tasks.

EX:

IBM Deep Blue: IBM’s reactive AI machine Deep Blue was able to read real-time cues in order to beat Russian chess grandmaster Garry Kasparov in a 1997 chess match.?

Netflix Recommendation Engine: Media platforms like Netflix often utilize AI-powered recommendation engines, which process data from a user’s watch history to determine and suggest what they would be most likely to watch next.

• Limited Memory AI:?AI that can store knowledge and use it to learn and train for future tasks.The core of limited memory AI is deep learning, which imitates the function of neurons in the human brain. This allows a machine to absorb data from experiences and “learn” from them, helping it improve the accuracy of its actions over time.?

Today, the limited memory model represents the majority of AI applications. It can be applied in a broad range of scenarios, from smaller scale applications, such as chatbots, to self-driving cars and other advanced use cases.

• Theory of Mind AI:?AI that can sense and respond to human emotions, plus perform the tasks of limited memory machines.Theory of mind could bring plenty of positive changes to the tech world, but it also poses its own risks. Since emotional cues are so nuanced, it would take a long time for AI machines to perfect reading them, and could potentially make big errors while in the learning stage. Some people also fear that once technologies are able to respond to emotional signals as well as situational ones, the result could mean automation of some jobs.
• Self-Aware AI

Self-aware AI describes artificial intelligence that possesses self-awareness. Referred to as the AI point of singularity, self-aware AI is the stage beyond theory of mind and is one of the ultimate goals in AI development. It’s thought that once self-aware AI is reached, AI machines will be beyond our control, because they’ll not only be able to sense the feelings of others, but will have a sense of self as well.?Perhaps one of the most famous of these is Sophia, a robot developed by robotics company Hanson Robotics.