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Types of ai

Chaos Theory
Chaos Theory

While understanding Chaos Theory is not strictly necessary for dealing with neural nets and the like, ... How do I start learning artificial intelligence?

source: quora.com
Computational Creativity –
Computational Creativity –

Computational creativity (also known as artificial creativity, mechanical creativity, creative computing or creative computation) is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence, cognitive psychology, philosophy, and the arts.

image: youtube.com
Evolutionary Computation, Including
Evolutionary Computation, Including

Evolutionary computation vs. deep learning. Evolutionary computation differs from deep learning in a number of ways, but the biggest difference is that deep learning is focused on modeling what we know — supervised training on an existing data set — whereas evolutionary computation is focused on creating solutions that do not yet exist.

Fuzzy Systems –
Fuzzy Systems –

Fuzzy Logic Systems (FLS) produce acceptable but definite output in response to incomplete, ambiguous, distorted, or inaccurate (fuzzy) input. What is Fuzzy Logic? Fuzzy Logic (FL) is a method of reasoning that resembles human reasoning.

Machine Learning
Machine Learning

There is little doubt that Machine Learning (ML) and Artificial Intelligence (AI) are transformative technologies in most areas of our lives. While the two concepts are often used interchangeably there are important ways in which they are different.

source: forbes.com
Probabilistic Methods Including
Probabilistic Methods Including

Similarly, showing that the probability is (strictly) less than 1 can be used to prove the existence of an object that does not satisfy the prescribed properties. Another way to use the probabilistic method is by calculating the expected value of some random variable.

Type I AI: Reactive Machines
Type I AI: Reactive Machines

Type I AI: Reactive machines The most basic types of AI systems are purely reactive, and have the ability neither to form memories nor to use past experiences to inform current decisions. Deep Blue, IBM’s chess-playing supercomputer, which beat international grandmaster Garry Kasparov in the late 1990s, is the perfect example of this type of machine.

Type II AI: Limited Memory
Type II AI: Limited Memory

Type IV AI: Self-awareness. The final step of AI development is to build systems that can form representations about themselves. Ultimately, we AI researchers will have to not only understand consciousness, but build machines that have it. This is, in a sense, an extension of the “theory of mind” possessed by Type III artificial intelligences.

image: xataka.com
Type III AI: Theory of Mind
Type III AI: Theory of Mind

Type III AI: Theory of mind. We might stop here, and call this point the important divide between the machines we have and the machines we will build in the future. However, it is better to be more specific to discuss the types of representations machines need to form, and what they need to be about.

Type IV AI: Self-Awareness
Type IV AI: Self-Awareness

Type IV AI: Self-awareness. The final step of AI development is to build systems that can form representations about themselves. Ultimately, we AI researchers will have to not only understand consciousness, but build machines that have it. This is, in a sense, an extension of the “theory of mind” possessed by Type III artificial intelligences.

image: futurism.com