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Functional AI

[Topics for Research in AI -]

- Overview

Functional AI uses advanced algorithms to help people and businesses make better decisions. It's similar to analytic AI, which scans large amounts of data to find patterns and dependencies. However, functional AI takes action instead of providing recommendations. 

Functional AI interacts with human thoughts and emotions, focusing on people whose minds can be shaped by many factors. It can understand complex situations and generate decision-making options to help people make better decisions that lead to desired outcomes. 

AI is the combination of algorithms that creates machines with human-like skills. It allows machines to learn from experience, adjust to new inputs, and perform human-like tasks. For example, chess-playing computers and self-driving cars use deep learning and natural language processing.

The four primary types of AI are: reactive, limited memory, theory of mind, and self-aware.


- Understanding the Types of AI

AI’s rapid growth and powerful capabilities have made people paranoid about the inevitability and proximity of an AI takeover. Also, the transformation brought about by AI in different industries has made business leaders and the mainstream public think that we are close to achieving the peak of AI research and maxing out AI’s potential. 

However, understanding the types of AI that are possible and the types that exist now will give a clearer picture of existing AI capabilities and the long road ahead for AI research.

Machines understand verbal commands, distinguish pictures, drive cars and play games better than we do. These intelligent systems are able to handle huge amounts of data and make complex calculations very quickly. 

But they lack an element that will be key to building the "sentient machines" we picture having in the future. We need to do more than teach machines to learn. 

- Understanding the Types of AI Classification

There are many terms and definitions in the field of AI, which make it difficult to distinguish categories from subsets or types of AI. Since AI research aims to make machines mimic the functions of humans, the degree to which an AI system can replicate human capabilities is used as a criterion for determining the type of AI.

Therefore, AI can be classified as one of several types of AI, depending on how machines compare to humans in terms of versatility and performance. Under such a system, an AI capable of performing more human-like functions with equal proficiency would be considered a more evolved AI, while an AI with limited functionality and performance would be considered a simpler and more evolved AI A lower level of artificial intelligence.

Based on this criterion, there are two ways in which AI is generally classified. One type is based on classifying AI and AI-enabled machines based on their likeness to the human mind, and their ability to “think” and perhaps even “feel” like humans. 

According to this classification system, there are four types of AI or AI-based systems: reactive machines, finite memory machines, theory of mind, and self-aware AI. We need to overcome the boundaries that define the four different types of AI, and the barriers that separate machines from us - and us from them.


- Reactive Machines 

Reactive machines are the oldest and most fundamental form of AI systems. These machines are very limited. Their inability to create memories or use past experience to shape current decisions means these systems cannot "learn" and do not improve over time.

They have zero conception of the past. They exist in the ultimate moment of the present, responding only to the world at that precise moment, not any internally created perception of the world.

Reactive machines are fundamental because they do not store "memory" or use past experience to determine future actions. They just perceive the world and react to it. IBM's Deep Blue defeated chess grandmaster Kasporov, a reaction machine that sees pieces on the board and reacts to them. It cannot refer to any previous experience and cannot be improved with practice.


Emerald Lake_121923A
[Emerald Lake, Yoho National Park, Canada]

- Limited Memory

Limited memory AI learns from the past and builds up empirical knowledge by observing actions or data. This type of AI uses historical observational data combined with preprogrammed information to make predictions and perform complex classification tasks. It is the most widely used type of artificial intelligence today.

Self-driving cars, for example, use AI with limited memory to observe the speed and direction of other cars, helping them "read the road" and adjust as needed. This process of understanding and interpreting incoming data makes them safer on the road.

However, AI with limited memory - as the name suggests - is still limited. The information used by self-driving cars is ephemeral and not kept in the car's long-term memory.


- Theory of Mind 

We have yet to reach Theory of Mind AI types. Theory of Mind AI is widely used in artificial emotional intelligence, and soon it will be used in other branches of AI as well.

As we mentioned above, the first two types of AI are already being implemented. Theory of Mind is the third category of AI, the next level of AI systems in the innovation stage. This type of artificial intelligence interacts with human thoughts and emotions.

This AI will basically focus on individuals whose minds can be shaped by a variety of factors, such as understanding humans. Theory of Mind AI will gain a better understanding of the entities they interact with by understanding their needs, thought processes, emotions, and beliefs.

"Understanding" is the main concept associated with Theory of Mind. It can deal with various aspects such as behavior, emotion, human nature and feelings, etc. This is considered one of the key technological developments in classifying people's moods, moods and thoughts.


- Self-Awareness

The final step in AI development is building systems that can form self-representations. Ultimately, we AI researchers will have to not only understand consciousness, but also build machines that possess it. In some distant future, perhaps artificial intelligence has achieved Nirvana. It becomes self-conscious. 

This AI exists only in the story and, as stories often do, instills great hope and fear in the audience. Self-aware intelligence beyond humans has independent intelligence and, most likely, people will have to negotiate terms with the entities they create. What will happen, good or bad, is anyone's guess. 

In a sense, this is an extension of the "theory of mind" that the third category of AI possesses. Consciousness is also called "self-awareness" for a reason. ("I want that item" is quite different from "I know I want that item.") Conscious people know themselves, know their internal state, and are able to predict how others will feel. We assume the person who honks behind us in traffic is angry or impatient because that's how we feel when we honk at others. We cannot make these inferences without a theory of mind.

While we may be far from creating self-aware machines, we should focus our efforts on understanding memory, learning, and the ability to make decisions based on past experience. This is an important step towards understanding human intelligence itself. This is critical if we want to design or evolve machines that are very good at sorting what is in front of them.


[More to come ...]

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