Decoding the History of artificial intelligence: 10 pivotal dates in AI evolution

Decoding the History of artificial intelligence: 10 pivotal dates in AI evolution

Artificial Intelligence (AI), although ubiquitous in our modern daily lives, has a complex history dating back several decades. It is the result of constant evolution.

To better understand this technological revolution, let’s delve into the history of AI through ten key dates that have shaped its trajectory.

Beyond historical facts, this exploration will help grasp how AI has influenced various fields, from chess strategy to precision facial recognition.

Artificial Intelligence in 10 Key Dates

  • 1943: McCulloch and Pitts lay the foundations of neural networks

Warren McCulloch and Walter Pitts publish “A Logical Calculus of Ideas Immanent in Nervous Activity,” laying the theoretical foundations of neural networks. Their model draws inspiration from the workings of the human brain, describing how artificial neurons can be connected to perform logical calculations.

  • 1951: Birth of the first neural network computer, SNARC

Mathematician Marvin Minsky and neurophysiologist Warren McCulloch construct the first neural network computer, the Stochastic Neural Analog Reinforcement Calculator (SNARC). Although rudimentary compared to current technologies, SNARC marks the concrete beginning of implementing neural network concepts in machines.

  • 1956: Dartmouth Conference gives birth to AI studies

The conference, organized by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon, brings together researchers to discuss the possibilities of creating “artificial intelligence.” It is the formal starting point of AI as a distinct field of study, with researchers like McCarthy playing a key role in AI development.

  • 1957: Creation of the first learning neural network, the Perceptron

Frank Rosenblatt develops the Perceptron, a simple neural network capable of learning to recognize patterns. Although its capabilities are limited, the Perceptron is a major breakthrough in showing that a neural network can adjust to improve its performance.

  • 1965: Weizenbaum develops a natural language processing program

Joseph Weizenbaum creates ELIZA, a natural language processing program simulating conversation. ELIZA generates significant interest by showing how a machine can interact with humans conversationally, anticipating the future development of chatbots.

  • 1997: IBM’s Deep Blue supercomputer beats the world chess champion

Deep Blue, a supercomputer designed by IBM, wins a historic match against world chess champion Garry Kasparov. This event marks a turning point by demonstrating that machines can outperform human champions in complex and strategic domains.

  • 2002: iRobot introduces Roomba, the first home vacuum robot based on AI

iRobot launches Roomba, a vacuum robot equipped with an AI-based navigation system. Roomba represents a significant advance in the practical application of AI in everyday life, providing an autonomous solution for a common household task.

  • 2014: Facebook creates DeepFace, a precision facial recognition software

Facebook develops DeepFace, a facial recognition system that achieves a level of accuracy close to human capability. This advancement underscores the potential of AI in computer vision and sparks discussions on ethical issues related to privacy.

  • 2020: OpenAI launches GPT-3, a major breakthrough in natural language processing

OpenAI unveils GPT-3 (Generative Pre-trained Transformer 3), a revolutionary language model based on pre-trained transformations. GPT-3 represents a breakthrough in machine understanding of natural language, opening new possibilities in text generation and human interactions.

  • 2021: DeepMind achieves a major breakthrough in protein folding for medical purposes

DeepMind, a subsidiary of Google, uses AI to solve the problem of protein folding, a complex task in biology. This breakthrough has significant implications for medical research and illustrates the potential of AI in solving crucial scientific problems.

Revisiting these key moments in the history of artificial intelligence, we witness a remarkable evolution, where abstract ideas have been translated into concrete advancements that redefine our relationship with technology.

What does 2024 hold for AI?

The possibilities seem endless, whether in improving existing applications or discovering new areas of exploration. The next steps could involve closer collaboration between AI and other emerging technologies or unexpected breakthroughs that will further expand our understanding and utilization of this technology.

But the impact of AI also extends beyond technical spheres to infiltrate our culture. From algorithm-generated artistic works to AI-powered virtual reality experiences, this technology plays an increasingly central role in the cultural sector. At Ask Mona, we place the latest AI technologies in the hands of cultural institutions to enhance visitor and collaborator experiences. Since 2017, over 100 institutions have trusted us, allowing AI to transcend the boundaries of what is possible, creating innovative and engaging cultural experiences.

Follow us for more information on how artificial intelligence serves the cultural sector!