What Is Artificial Intelligence (AI)?

The concept of “a maker that believes” go back to ancient Greece. But considering that the development of electronic computing (and relative to a few of the topics talked about in this post) essential events and milestones in the evolution of AI include the following:

1950.
Alan Turing releases Computing Machinery and Intelligence. In this paper, Turing-famous for breaking the German ENIGMA code during WWII and typically described as the “dad of computer science”- asks the following concern: “Can machines think?”

From there, he uses a test, now notoriously understood as the “Turing Test,” where a human interrogator would try to distinguish in between a computer system and human text action. While this test has actually undergone much examination since it was released, it remains a fundamental part of the history of AI, and a continuous idea within philosophy as it uses concepts around linguistics.

1956.
John McCarthy coins the term “expert system” at the first-ever AI conference at Dartmouth College. (McCarthy went on to invent 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.
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 release a book titled Perceptrons, which becomes both the landmark work on neural networks and, at least for a while, an argument versus future neural network research study efforts.

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

1995.
Stuart Russell and Peter Norvig publish Artificial Intelligence: A Modern Approach, which becomes one of the leading books in the study of AI. In it, they look into four prospective goals or meanings of AI, which differentiates computer 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 writes a paper, What Is Expert system?, and proposes an often-cited definition of AI. By this time, the era of big data and cloud computing is underway, making it possible for organizations to handle ever-larger data estates, which will one day be utilized to train AI designs.

2011.
IBM Watson ® beats champs Ken Jennings and Brad Rutter at Jeopardy! Also, around this time, information science starts to emerge as a popular discipline.

2015.
Baidu’s Minwa supercomputer uses an unique deep neural network called a convolutional neural network to identify 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 victory is significant given the huge variety of possible moves as the game advances (over 14.5 trillion after simply four moves). Later, Google purchased DeepMind for a reported USD 400 million.

2022.
A rise in big language models or LLMs, such as OpenAI’s ChatGPT, creates a massive change in efficiency of AI and its possible to drive business value. With these brand-new generative AI practices, deep-learning models can be pretrained on large quantities of information.

2024.
The newest AI trends indicate a continuing AI renaissance. Multimodal designs that can take several kinds of information as input are offering richer, more robust experiences. These designs unite computer system vision image recognition and NLP speech recognition abilities. Smaller models are likewise making strides in an age of diminishing returns with enormous models with large specification counts.