What Is Artificial Intelligence (AI)?

The concept of “a machine that believes” go back to ancient Greece. But because the introduction of electronic computing (and relative to some of the topics discussed in this short article) essential events and turning points 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 often described as the “father of computer technology”- asks the following question: “Can makers believe?”

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 undergone much examination considering that it was released, it stays a fundamental part of the history of AI, and an ongoing idea within approach 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 produce the Logic Theorist, the first-ever running AI computer program.

1967.
Frank Rosenblatt constructs the Mark 1 Perceptron, the very first computer system based upon a neural network that “discovered” through experimentation. Just a year later, Marvin Minsky and Seymour Papert release a book titled Perceptrons, which ends up being both the landmark work on neural networks and, at least for a while, an argument versus future neural network research efforts.

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

1995.
Stuart Russell and Peter Norvig publish Artificial Intelligence: A Modern Approach, which turns into one of the leading books in the research study of AI. In it, they explore four potential 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 writes a paper, What Is Artificial Intelligence?, and proposes an often-cited definition of AI. By this time, the era of big information and cloud computing is underway, making it possible for companies to manage ever-larger information estates, which will one day be used to train AI models.

2011.
IBM Watson ® beats champions 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 an unique deep neural network called a convolutional neural network to recognize and categorize 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 gamer, in a five-game match. The triumph is considerable given the huge variety of possible relocations as the game advances (over 14.5 trillion after just four moves). Later, Google acquired DeepMind for a reported USD 400 million.

2022.
An increase in big language designs or LLMs, such as OpenAI’s ChatGPT, produces a massive modification in performance of AI and its prospective to drive enterprise value. With these new generative AI practices, deep-learning designs can be pretrained on large quantities of information.

2024.
The latest AI trends indicate a continuing AI renaissance. Multimodal designs that can take numerous kinds of data as input are providing richer, more robust experiences. These models combine computer vision image recognition and NLP speech acknowledgment abilities. Smaller designs are also making strides in an age of reducing returns with huge designs with large parameter counts.