Artificial intelligence applications

 

Artificial intelligence

     Artificial intelligence is one of the branches of computer science, and is defined as certain characteristics and behavior of computer programs that cause it to simulate human mental abilities and work patterns.   The most prominent of these characteristics is the ability to reason, learn, and respond to situations that are not programmed into the machine. Smart customers.

     artificial intelligence applications

Use it in a wide range of areas, such as: expert systems, medical diagnostics, Internet search engines, natural language processing, video games, stock trading, law, image recognition and analysis, gaming, scientific discovery, automation and recognition of voice.  

• History of artificial intelligence

•      In the mid-20th century AD, scientists began to explore a new approach to building intelligent machines, and based on recent discoveries in neuroscience and the development of cybernetics through the invention of the digital computer, machines that can simulate the process.   of human computational thinking were invented.

•      The modern field of artificial intelligence research was established in 1956 AD. C. when a conference was held on the Dartmouth College campus, and prominent leaders in artificial intelligence research included Marvin Minsky, Herbert Simon, John McCarthy, and Allen Noel.  

•      Beginning in the 1980s, AI research saw a new interest with the commercial success of expert systems, which are artificial intelligence programs that simulate the analytical skills and knowledge of one or more human experts.  

•      Artificial intelligence achieved great successes in the 1990s and early 2000s. Where AI has been used in data mining, logistics, the technology industry, and medical diagnostics.

The philosophy of artificial intelligence

•      Honda Asimo Robot: AI Inspires and Challenges Philosophy; Because it has the ability to recreate the capabilities of the human mind.

•      Turing's Law (computing machines and intelligence): we judge the intelligence of a machine based on its performance; It is as if the device works with an intelligence comparable to that of a human being, since its intelligence is similar to that of a human being.  

• Dartmouth's thesis: every aspect of the learning process is a manifestation of intelligence that allows a human being to design a machine to simulate it.

•      Gödel's Incompleteness Theorem: No logical system can prove that all sentences are true. Roger Penrose and others believe that this theory does not set limits to what a person can do, but limits to what machines can do.

•      The premise of Noel and Simon's physical symbol system: The essence of intelligence lies in the ability to process symbols.

•      The artificial brain hypothesis: Ray Kurzweil, Hans Morwijk and others say that it is technically possible to copy the brain directly into software and hardware.

•      Searle's Strong AI Hypothesis: Known as the Chinese room, it focuses on the possibility that a computer could have a human-like mind if programmed correctly with the correct inputs and outputs.