Types of Artificial intelligence that you  should know now

I plan to write another detailed post about this aspect of AI in the future as understandable explanation does not fit in single article hence check out complete list of what neural networks can do here, according to my research the several types of Artificial intelligence that you should know are given below.

AI is rapidly developing and has already proved its strong potential to revolutionize anything from the way industries function, but also on how we do things on a daily basis. AI is already having a big impact on our world, everywhere from voice assistants to self-driving cars. But AI is not a panacea; it exists in different versions with their own unique strengths and uses. This blog post encompasses four types of AI classified based on capability, functionality, applications as well as techniques.

1. Based on Capability

Narrow AI (Weak AI):

Most of the so called AI today is Narrow AI. Their purpose is to make a lot of predictions. Say, on images — where the things are located or what they might represent; similar kinds as when you hear Siri talking back at your commands in real time! Even if highly powerful in its domain, Narrow AI cannot perform tasks outside of it.

General AI (Strong AI):

General AI: This is the hypothetical form of AI can do any intellectual task that a human being can accomplish. Whereas General AI could comprehend, learn and utilize knowledge across different domains where as the same is not true for Narrow AI. General AI is also known as Strong AI and this concept has not been achieved yet, but widely depicted in science fictions.

Super AI:

AI — that is smarter than human in all dimensions -in creativity, problem solving, emotional intelligence etc.

2. Based on Functionality

Reactive Machines:

The simplest type of AI is reactive machines. All they can do is react to present circumstances: They are unable even remember old ones or learn from past mistakes. Prime among them is IBM's Deep Blue, the computer that beat world champion Garry Kasparov in chess. It was able to simulate possible state changes, but it had zero awareness of history or known strategies.

Limited Memory:

Many AI systems today belong to this class. While that may seem like a capability, limited memory AI can only make decisions based on it with no way to store and apply the information for other tasks. A common example falls in the domain of self-driving cars that use data from previous trips to drive, maintain safety and avoid obstacles.

Theory of Mind:

This is something called Theory of Mind AI that, as far as we know, only exists in research. Initiative of learning automated machine which can comprehend human sentiments, beliefs [5] and intentions. An AI like this would be able to communicate with humans more naturally and intuitively, detecting subtle social cues.

Self-Aware AI:

They will have awareness and reflectiveness, — the highest form of artificial intelligence you can think of. Very exciting shit, but still speculative and fraught with all kinds of philosophical questions on the nature of consciousness as well as possible ethical concern about creating self aware machines.

 3. Based on Applications

Artificial General Intelligence AGI — a machine that can apply common sense across all its specific tasks .Artificial Narrow Intelligence ANI — a super intelligent task-efficient computer.

ANI (Narrow AI) — which is designed to perform a singular task, or narrow set of tasks The IC system (IC-AI) is the most common form of AI in use today, examples including language translation and fraud detection. While ANI can be strong within their specific domain but cannot replicate those capabilities in other fields.

Arial General intelligence (AGI)

AGI engenders the notion of forming devices that can believe and became identical to individuals. This lets AGI take any intelligible task a human could theoretically perform and understand/learn in almost every domain. AGI is a long-way-off pursuit of AI research.

Super Artificial General Intelligence (ASI):

ASI is further than AGI, being AI that totally surpasses human intelligence. The potential of ASI to transform entire industries, address vast complex global problems and even alter the course of human history is extraordinary. Yet the technology suggests existential threats, and it demands to be handled with care (and regulation).

Read more : Ai intelligence and Human Mind

 4. Based on Techniques

Machine Learning (ML):

AI is the broader concept that has aimed at letting machines carry out tasks in which human intelligence performs such as visual perception, speech recognition, decision-making and language translation etc by Machine Learning; a subset of AI based on giving data to machine and it learns from this dataset. Over time, ML algorithms get better with more data. There are three main subtypes of ML — supervised learning, unsupervised learning and reinforcement learning that each has a unique way they learn from data.

Deep Learning:

Deep Learning — Deep learning is a subset of ML, in which neural networks with multiple layers (hence "deep") are used to learn and then model complex patterns within large data sets. It has found great success in tasks such as image recognition, natural language processing, and game-playing. Deep Learning has been responsible for many recent successes in AI.

NLP — Natural Language Processing:

NLP stands for Natural Language Processing, and it is a field of Artificial Intelligence (AI) concerned with the interaction between computers and human language. It involves an enormous of applications from chatbots to language translation, sentiment analysis and speech recognition. NLP tries to help us with the ways that we — as humans, in substantially different cultures and languages—understand meaning from human language (so-called natural-language text) where that is not merely entertainment or art but also informative CP 3.

Computer Vision:

Computer Vision: The part of AI that permits a machine to interpret and understand visual data, at making decisions accordingly. Some real-world examples of computer vision are facial recognition, object detection and autonomous driving applications Computer vision systems can see the world and act on it through processing of images and videos.

Expert Systems:

Expert systems are AI applications that solve a specialized problem within a small domain>:: they provide meaningful answers (i.e., explanations), and they can adapt, learn from experience or be reprogrammed::[79] They are one that can mimic the capabilities of a human expert such as decision-making and often used to recommend solutions or suggestions includes medicine, finance, engineering etc.

FAQs

1. 5 Major types of AI

That is, AI are categorized in Narrow intelligence, General Intelligence and Superintelligence. It can also be broken divided based on function (Reactive Machines, Limited Memory, Theory of Mind, Self-Aware AI) and based-on learning tools it might fall into categories for Machine Learning -> Deep Learning — NLP… etc.

2. What is Narrow AI?

Weak AI (or Narrow AI) — this type of artificial intelligence is built for a narrow specific task. For Zorrilla, it could be facial recognition or voice assistants such as Siri. This is the widest-used type of AI out there currently.

3. What is General AI?

A General AI is one can perform any intellectual task that a human being can. That is still a very hypothetical and distant AIMETA.

4. What is Super AI?

Artificial Intelligence Becomes Smarter Than Humans Everywhere It is a theoretical concept which has yet to be realized.

5. Where Does Machine Learning Fit In With AI?

Machine Learning, a type of Artificial Intelligence (AI) that empowers systems to learn from data and experience without being explicitly programmed.

6. What is Deep Learning?

Deep Learning is a sub-type of Machine Learning using neural networks with many layers, and it works quite well in image recognition and natural language processing.

7. ANI vs AGI vs ASI

ANI: Specializes In Narrow Tasks (90% of AI we know today)

Human-like cognitive power AGI (theoretical)

Super ASI: Exceeds your intelligence in all domain, theoretical also.

 Conclusion

The field of artificial intelligence applications Potential seems impossibly mature. However, it also means we appreciate the current capabilities of today's AI and know what to expect in the future. With AI now in its fifth decade of development, the evolution from Narrow Artificial to a prospective Super AGI is taking place at rapid speed opening up numerous opportunities and challenges.

AI technology will require ethical considerations and responsible development alongside its great potential. But across a sort of different aspect for our life, whether we're talking to any voice assistance, AI-based medical diagnosis or even imagining intelligent robots future.