types and future of ai machine learning technology

types and future of ai machine learning technology
18/08/2021 No Comments News, TECH Anshul
  • Here We are Giving complete list of types and future of ai machine learning technology

What is ai machine learning technology -Types, History and Future:-

  • Artificial intelligence (AI) is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and artificial intelligence:- and deep learning are creating a paradigm shift in virtually every sector of the tech industry. 

7 types of AI explained:-

Reactive machines

Reactive machines are the most basic types of AI systems that perceive the world directly and act on what it sees. The computer is purely reactive, and neither has to form memory nor to use past experience. AI researcher Rodney Brooks argued in a seminal paper that we should only build this kind of AI. For example, Deep Blue, IBM’s chess-playing supercomputer that made a breakthrough by beating grandmaster Garry Kasparov in 1997 was a reactive machine. It did not take any pre-applied datasets or look for previous matches. All it knows was how to play the game and conditions. The computer moved chess coins based on its real-time intuition and won the game.

Limited Memory

Limited memory machines are ditto of reactive machines added with historical data which will help them take decisions. Almost all the machines that we use today are limited memory machines, which are powered by datasets. AI systems use deep learning and are trained by large volumes of data that they store in their memory to form a reference model for solving future problems. For example, an image recognition AI is trained to determine and label certain things like a cat or a dog from a picture. It knows how a cat or a dog looks from the previously trained datasets. Henceforth, it opts out the matching images.

Theory of mind

As the name sounds, the theory of mind machines represents an advanced class of technology and exists only as a concept. This kind of AI requires a thorough understanding of people’s and thing’s feelings and behaviour within an environment. Theory of minds is a critical technological improvement that sorts people’s emotions, sentiments and thoughts. Even though many improvements are made to reach this stage of AI, it is not fully completed. A real-world example of the theory of mind is Kismet, designed in the late 1990s. Kismet can mimic human emotions and recognise them.


Self-aware AI is the exact thing that is portrayed in AI-movies. The critical AI robots that think on their own and destroy humans are the ideology-driven from self-aware AI. However, we can’t predict that all might go bad. There are also chances that the futuristic AI might go hand-in-hand with humans. Even though it is impossible for now, self-aware AI is on the bucket list for many scientists. Tech personalities like Elon Musk and Stephen Hawkings have consistently warned us about the evolution of AI which could reach the self-aware stage.

Artificial Narrow Intelligence (ANI)

it is also known as ‘week AI’ is one of the most frequently experienced types of AI. It is something that the tech world has accomplished. Every AI machine we use and see today is from this field, which operates under a limited set of constraints. For example, voice recognition AI is used to predict people’s voice based on the dataset it is trained with. The deep learning model constitutes the ‘Limited Memory’ type and similar tasks could be a case of ‘Reactive Machines.’

Artificial General Intelligence (AGI)

it is also known as ‘strong AI’ allows a machine to apply knowledge and skills in different contexts. This more closely mirrors human intelligence by providing opportunities for autonomous learning and problem-solving. In other words, AGI can successfully perform any intellectual task that a human being can.

Artificial Super Intelligence (ASI)

it is something more advanced than ‘strong AI’ which could end the human race. They will not only replicate the multi-faceted intelligence of human beings but will be exceedingly better at everything. The ASI will be designed with better memory, faster data processing and analysis, and decision-making capabilities.

What is machine learning technology -Types, History and Future:

Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.

10 -Types of machine learning technology

1. Supervised Learning

 It is describes a class of problem that involves using a model to learn a mapping between input examples and the target variable.

2.Reinforcement Learning

It describes a class of problems where an agent operates in an environment and must learn to operate using feedback.

3. Semi-Supervised Learning

Semi-supervised learning is supervised learning where the training data contains very few labeled examples and a large number of unlabeled examples.

4. Multi-Instance Learning

Multi-instance learning is a supervised learning problem where individual examples are unlabeled; instead, bags or groups of samples are labeled.

5. Multi-Task Learning

Multi-task learning is a type of supervised learning that involves fitting a model on one dataset that addresses multiple related problems.

6. Active Learning

Active learning is a technique where the model is able to query a human user operator during the learning process in order to resolve ambiguity during the learning process.

7. Transductive Learning

Transduction or transductive learning is used in the field of statistical learning theory to refer to predicting specific examples given specific examples from a domain.

8. Online Learning

Online learning involves using the data available and updating the model directly before a prediction is required or after the last observation was made.

9.Ensemble Learning

Ensemble learning is an approach where two or more modes are fit on the same data and the predictions from each model are combined.

10.Transfer Learning

Transfer learning is a type of learning where a model is first trained on one task, then some or all of the model is used as the starting point for a related task.

What is the future of AI And Ml:

Artificial intelligence is impacting the future of virtually every industry and every human being. Artificial intelligence has acted as the main driver of emerging technologies like big data, robotics and IoT, and it will continue to act as a technological innovator for the foreseeable future.

Machine Learning:
Basically, it’s an application of artificial intelligence. Also, it allows software applications to become accurate in predicting outcomes. Moreover, machine learning focuses on the development of computer programs. … Google says” Machine Learning is the future”, so future of machine learning is going to be very bright.

So this is all about the list of types and future of ai machine learning technology

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