What is AI and how does it work
Artificial intelligence (AI) is the ability of a computer program or system to behave with intelligence like that of a human. There are three levels of AI that our current technology has enabled.
Weak AI can simulate some aspect(s) of human intelligence, but the design makes no attempt to emulate all the abilities necessary for actual thinking in humans. For weak AI, developers will target either very specific tasks or multiple related tasks. One example would be voice recognition software that can perform speech transcription, understand and answer simple questions posed in natural language, and summarize spoken sections underneath interactive online text captions that accurately link back to appropriate times in the audio feed.
Weak AI does not have general application knowledge and therefore cannot perform multiple independent activities without specific instructions.
Knowledge-based AI is able to apply a limited range of intelligence using domain knowledge, but the application may be so narrow that it would be unreasonable to consider it reasoning or learning in any meaningful sense. The term "weak AI" has also been used synonymously with this definition, but many researchers now regard weak and knowledge-based AIs as distinct categories of AI. The term "weak AI" was coined in the 1960s and used throughout the 1980s to describe a project that aimed to create programs that could solve specific problems without error, but with little reasoning or learning ability beyond what was explicitly programmed into them.
In general, commonly used methods for representing knowledge of expert systems can be classified into these categories:
Deep learning is a branch of machine learning that uses artificial neural networks with multiple hidden layers of units to give computers the ability to learn without being explicitly programmed. Neural networks were inspired by the structure of neurons in a biological brain. The common types of artificial neural networks are perceptron's, multi-layer perceptron's, radial basis function networks, and convolutional neural networks.
The human brain is made up of billions of cells called neurons which send signals to other neurons using electrochemical messengers called neurotransmitters. The human brain has about 100 billion (10) neurons and each one is connected with thousands of other neurons and so a typical neuron makes about 10,000 connections to other neurons.
Artificial neural networks are computer models that are inspired by the structure of biological brains such as the human brain and also work in a similar way. They are made up of large number of units which act like neurons, these units are connected to each other through connections and they send signals along these connections.
Neural networks have been used for speech recognition since 1988 when researchers at IBM used a neural network called "WATSON " to help in the understanding of spoken letters.
Artificial Intelligence is an incredibly exciting field with many opportunities for growth and innovation.
There are a lot of resources out there to help you stay on top of the latest AI developments, so we’ve compiled some helpful links that may be worth bookmarking or following if you want to learn more about this topic.
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