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  • Founded Date May 28, 1978
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What Is Artificial Intelligence (AI)?

The idea of “a maker that believes” dates back to ancient Greece. But given that the arrival of electronic computing (and relative to a few of the topics talked about in this post) crucial occasions and turning points in the development of AI include the following:

1950.
Alan Turing publishes Computing Machinery and Intelligence. In this paper, Turing-famous for breaking the German ENIGMA code throughout WWII and often referred to as the “dad of computer science”- asks the following question: “Can machines think?”

From there, he offers a test, now famously referred to as the “Turing Test,” where a human interrogator would attempt to compare a computer system and human text action. While this test has actually gone through much examination since it was released, it remains a vital part of the history of AI, and a continuous concept within approach as it utilizes ideas 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 develop the Logic Theorist, the first-ever running AI computer system program.

1967.
Frank Rosenblatt constructs the Mark 1 Perceptron, the first computer system based upon a neural network that “discovered” through trial and mistake. Just a year later on, Marvin Minsky and Seymour Papert publish a book entitled Perceptrons, which ends up being both the landmark deal with neural networks and, a minimum of for a while, an argument versus future neural network research initiatives.

1980.
Neural networks, which utilize a backpropagation algorithm to train itself, became commonly utilized in AI applications.

1995.
Stuart Russell and Peter Norvig release Expert system: A Modern Approach, which turns into one of the leading textbooks in the study of AI. In it, they explore four prospective objectives or meanings of AI, which separates computer system 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 composes a paper, What Is Expert system?, and proposes an often-cited meaning of AI. By this time, the period of huge information and cloud computing is underway, enabling organizations to manage ever-larger data estates, which will one day be utilized to train AI designs.

2011.
IBM Watson ® beats champions Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, data science begins to become a popular discipline.

2015.
Baidu’s Minwa supercomputer uses an unique deep neural network called a convolutional neural network to recognize and categorize images with a higher rate of precision than the average human.

2016.
DeepMind’s AlphaGo program, powered by a deep neural network, Sodol, the world champ Go player, in a five-game match. The victory is significant offered the substantial number of possible moves as the video game advances (over 14.5 trillion after just 4 moves). Later, Google acquired DeepMind for a reported USD 400 million.

2022.
A rise in large language designs or LLMs, such as OpenAI’s ChatGPT, develops a huge modification in performance of AI and its possible to drive business worth. With these brand-new generative AI practices, deep-learning models can be pretrained on big quantities of information.

2024.
The latest AI trends point to a continuing AI renaissance. Multimodal models that can take multiple types of information as input are offering richer, more robust experiences. These models combine computer vision image recognition and NLP speech recognition abilities. Smaller designs are likewise making strides in an age of decreasing returns with huge models with large specification counts.