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Founded Date April 6, 1949
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What Is Artificial Intelligence (AI)?
The idea of “a machine that believes” dates back to ancient Greece. But given that the introduction of electronic computing (and relative to some of the topics talked about in this post) important events and milestones in the advancement of AI include the following:
1950.
Alan Turing publishes Computing Machinery and Intelligence. In this paper, Turing-famous for breaking the German ENIGMA code during WWII and frequently described as the “daddy of computer science”- asks the following question: “Can devices believe?”
From there, he provides a test, now notoriously called the “Turing Test,” where a human interrogator would try to compare a computer and human text action. While this test has undergone much examination because it was published, it remains a fundamental part of the history of AI, and a continuous idea within philosophy as it uses ideas around linguistics.
1956.
John McCarthy coins the term “synthetic intelligence” at the first-ever AI conference at Dartmouth College. (McCarthy went on to create the Lisp language.) Later that year, Allen Newell, J.C. Shaw and Herbert Simon develop the Logic Theorist, the first-ever running AI computer program.
1967.
Frank Rosenblatt constructs the Mark 1 Perceptron, the very first computer based on a neural network that “found out” through experimentation. Just a year later, Marvin Minsky and Seymour Papert publish a book titled Perceptrons, which becomes both the landmark work on neural networks and, a minimum of for a while, an argument against future neural network research study initiatives.
1980.
Neural networks, which use a backpropagation algorithm to train itself, became extensively utilized in AI applications.
1995.
Stuart Russell and Peter Norvig release Artificial Intelligence: A Modern Approach, which turns into one of the leading books in the research study of AI. In it, they dig into four possible goals or definitions of AI, which separates computer system systems based on rationality and thinking versus acting.
1997.
IBM’s Deep Blue beats then world chess champ Garry Kasparov, in a chess match (and rematch).
2004.
John McCarthy composes a paper, What Is Expert system?, and proposes an often-cited definition of AI. By this time, the period of huge information and cloud computing is underway, making it possible for companies to handle ever-larger data estates, which will one day be used to train AI models.
2011.
IBM Watson ® beats champs Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, data science starts to emerge as a popular discipline.
2015.
Baidu’s Minwa supercomputer utilizes a special deep neural network called a convolutional neural network to determine and classify images with a greater rate of accuracy than the average human.
2016.
DeepMind’s AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champion Go player, in a five-game match. The success is substantial provided the big variety of possible moves as the video game advances (over 14.5 trillion after simply four moves). Later, Google bought DeepMind for a reported USD 400 million.
2022.
A rise in large language models or LLMs, such as OpenAI’s ChatGPT, produces a massive modification in performance of AI and its possible to drive enterprise value. With these new generative AI practices, deep-learning models can be pretrained on large of information.
2024.
The most recent AI trends indicate a continuing AI renaissance. Multimodal designs that can take numerous kinds of data as input are supplying richer, more robust experiences. These models unite computer system vision image recognition and NLP speech recognition capabilities. Smaller designs are also making strides in an age of diminishing returns with huge models with large specification counts.