The idea of a “thinking machine” dates back to ancient Greece. However, since the advent of electronic computing (and compared to some of the topics discussed in this article), key events and milestones in the evolution of AI include:
1950
Alan Turing will be published Computing Machinery and Intelligence. In this paper, Turing, famous for breaking German Enigma Code during World War II, is often referred to as the “father of computer science.”
From there, he offers a test. It is now known as the “Turing Test.” Here, the human interrogator attempts to distinguish between computers and human textual responses. Although this test has undergone much scrutiny since its publication, it is an important part of the history of AI and remains an ongoing concept within a philosophy that uses ideas about linguistics.
1956
John McCarthy fills the term “artificial intelligence” at his first AI conference at Dartmouth University. (McCarthy continued to invent the LISP language.) Later that year, Allen Newell, J.C. Shaw, and Herbert Simon created the logic theorist, the first AI computer program ever.
1967
Frank Rosenblatt builds the Mark 1 Perceptron, the first computer based on a neural network that “learses” through trial and error. Just a year later, Marvin Minsky and Seymour Papert will publish a book entitled Perceptrons. This will be both a groundbreaking task of neural networks and, at least for some time, debate on future neural network research initiatives.
1980
Neural networks that train themselves using backpropagation algorithms have been widely used in AI applications.
1995
Stuart Russell and Peter Norvig Publish Artificial Intelligence: A Modern ApproachIt will be one of the major textbooks in AI research. In it, they dig into four potential goals or definitions of AI. This distinguishes computer systems based on rationality, thought and acting.
1997
IBM's deep blue beat, and world chess champion Garry Kasparov, chess matches (and rematches).
2004
John McCarthy writes his paper, What is artificial intelligence?and propose the often cited definitions of AI. By this time, the age of big data and cloud computing is ongoing, allowing organizations to manage more serious data estates, and one day they will be used to train AI models.
2011
IBM Watson® defeated champions Ken Jennings and Brad Rutter in Jeopardy! Also, around this time, data science began to emerge as a popular discipline.
2015
Baidu's Minwa SuperComputer uses a special deep neural network called convolutional neural networks to identify and classify images with greater accuracy than the average person.
2016
Powered by deep neural networks, Deepmind's Alphago program defeated world champion Go player Lee Sodol in five game matches. As the game progresses, victory is important given the vast number of possible moves (over 14.5 trillion after only four moves). Google then bought DeepMind for the reported US$400 million.
2022
Larger language models such as Openai's ChatGPT and the rise in LLMs will bring about a major change in the performance of AI and the potential to drive enterprise value. These new generation AI practices allow deep learning models to be preprocessed with large amounts of data.
2024
The latest AI trends show a continuous AI renaissance. Multimodal models that can retrieve multiple types of data as input provide a richer and robust experience. These models bring together computer vision image recognition and NLP speech recognition capabilities. Additionally, in an age where returns are reduced for large models with large parameters, smaller models are making progress.
