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Founded Date September 6, 2008
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What Is Artificial Intelligence (AI)?
The concept of “a maker that thinks” dates back to ancient Greece. But since the arrival of electronic computing (and relative to a few of the subjects talked about in this article) essential occasions 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 often referred to as the “father of computer science”- asks the following question: “Can makers believe?”
From there, he provides a test, now notoriously referred to as the “Turing Test,” where a human interrogator would try to differentiate in between a computer and human text action. While this test has actually gone through much examination since it was released, it remains a fundamental part of the history of AI, and a continuous principle within philosophy as it utilizes concepts around linguistics.
1956.
John McCarthy coins the term “expert system” 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 create the Logic Theorist, the first-ever running AI computer system program.
1967.
Frank Rosenblatt develops the Mark 1 Perceptron, the very first computer system based on a neural network that “learned” through trial and mistake. Just a year later on, Marvin Minsky and Seymour Papert publish a book entitled Perceptrons, which becomes both the landmark deal with neural networks and, a minimum of for a while, an argument against future neural network research study efforts.
1980.
Neural networks, which utilize a backpropagation algorithm to train itself, ended up being extensively used in AI applications.
1995.
Stuart Russell and Peter Norvig release Intelligence: A Modern Approach, which turns into one of the leading books in the research study of AI. In it, they dive into 4 possible objectives or definitions of AI, which distinguishes computer systems based on rationality and thinking versus acting.
1997.
IBM’s Deep Blue beats then world chess champion Garry Kasparov, in a chess match (and rematch).
2004.
John McCarthy writes a paper, What Is Expert system?, and proposes an often-cited meaning of AI. By this time, the age of huge information and cloud computing is underway, allowing companies to handle ever-larger information estates, which will one day be used to train AI designs.
2011.
IBM Watson ® beats champs Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, data science begins to become a popular discipline.
2015.
Baidu’s Minwa supercomputer utilizes a special deep neural network called a convolutional neural network to identify and categorize images with a higher rate of accuracy than the typical human.
2016.
DeepMind’s AlphaGo program, powered by a deep neural network, beats Lee Sodol, the world champ Go gamer, in a five-game match. The success is substantial given the huge variety of possible moves as the game progresses (over 14.5 trillion after just 4 moves). Later, Google purchased DeepMind for a reported USD 400 million.
2022.
An increase in big language designs or LLMs, such as OpenAI’s ChatGPT, produces a huge change in performance of AI and its potential to drive business value. With these new generative AI practices, deep-learning designs can be pretrained on large quantities of data.
2024.
The current AI patterns indicate a continuing AI renaissance. Multimodal designs that can take numerous types of data as input are offering richer, more robust experiences. These designs unite computer vision image acknowledgment and NLP speech acknowledgment abilities. Smaller models are likewise making strides in an age of decreasing returns with massive models with big parameter counts.