When did AI begin?

The field of artificial intelligence (AI) can be traced back to the 1950s, when researchers began to explore the idea of creating machines that could perform tasks that would normally require human intelligence...

When did AI begin?

When did AI begin? The term "artificial intelligence" was first coined in 1956 at the Dartmouth Conference, which is considered the birthplace of AI as a field of research.


Computer scientists :

At this conference, computer scientists John McCarthy, Marvin Minsky and others proposed the development of "thinking machines" that could mimic human intelligence and solve complex problems. The researchers hoped that AI would one day be able to perform tasks such as language translation, problem solving and pattern recognition.

AI research:

In the following decades, AI research made rapid progress in areas such as natural language processing, machine vision and machine learning. However, progress in AI research slowed down in the 1980s and 1990s due to limited computing power and the inability of early AI systems to solve complex tasks.

Advances in computing power:

In recent years, advances in computing power, data storage and machine learning algorithms have led to a resurgence of interest in AI. Today, AI is used in a wide range of applications, from virtual assistants and chatbots to self-driving cars and medical diagnostic devices.

When did AI begin?

The concept of artificial intelligence (AI) dates back to ancient times, but the modern era of AI began in the mid-20th century. The term "artificial intelligence" was coined by John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon at the Dartmouth Conference in 1956.

AI was marked by significant advances:

The early years of AI were marked by significant advances in the development of algorithms and models that could simulate human intelligence. One of the first examples of AI was the development of the first chess-playing computer program in the late 1940s. In the 1950s and 1960s, researchers developed symbolic AI, which used logic and rules to simulate human decision-making.

AI, in which researchers developed algorithms:

In the 1980s, machine learning became a popular approach in AI, where researchers developed algorithms that could learn from data and improve their performance over time. This approach led to significant advances in natural language processing, computer vision and robotics.

Deep learning:

Since then, AI has evolved rapidly, with Deep Learning becoming the dominant approach to machine learning and AI applications becoming more common in areas such as healthcare, finance and transport.