Did you know that years ago, the idea of a machine thinking like a human seemed closer to science fiction? It was merely a dream for researchers who believed in the possibility of building systems capable of learning, understanding, and making decisions.

But what was once just an idea on paper has become one of the most influential fields in the world today. Although many people interact with tools artificial intelligence on a daily basis, only a few know the full story behind this technological revolution; how did it start? Who are the scientists who laid its foundations? And what are the stages of AI evolution that brought us to the intelligent models we use today?

Therefore, in this article from Sard we will explore everything related to the history of artificial intelligence and the latest innovations driving the future of global technology.

What is artificial intelligence? And why has it become one of the most important technologies of our era?

Before diving into the history of artificial intelligence, it is important to understand what this term, which is now heard everywhere, actually means. Artificial Intelligence is a branch of computer science aimed at developing systems and software capable of performing tasks that typically require human mental capabilities, such as reasoning, learning, analysis, language understanding, and decision-making.

In simpler terms, artificial intelligence seeks to make machines more capable of understanding information and interacting with it intelligently, rather than just executing traditional commands. Modern AI capabilities include:

• Analyzing massive amounts of data.
• Recognizing images and sounds.
• Understanding human language.
• Predicting future outcomes.
• Learning from past experiences.
• Making complex decisions with speed and accuracy.

This is why artificial intelligence has become an essential part of the digital transformation currently being experienced by institutions, governments, and companies around the world.

The early beginnings of the idea: Did artificial intelligence start before the advent of computers?

Some might think that artificial intelligence emerged with computers, but the truth is that the foundation of the idea dates back centuries before the invention of the first computer. Since ancient times, humans have been fascinated by the idea of creating machines capable of performing tasks automatically or mimicking certain human abilities.

These notions appeared in ancient myths and stories about mechanical beings that could move and perform specific functions without direct human intervention, reflecting early human fascination with the concept of the “intelligent machine.” As civilizations evolved and science progressed, the idea moved from the realm of fantasy to the scope of scientific thought.

In the 17th and 18th centuries, scientists began developing mechanical calculators and establishing the foundations of mathematical logic, proving that certain mental processes could be converted into specific steps and rules that machines could execute.

During the 19th century, the world witnessed pivotal developments that paved the way for the later digital revolution. Mathematicians introduced new concepts related to algorithms and symbolic logic, and early designs for advanced calculating machines emerged, which many consider the intellectual foundation of modern computers.

All these achievements were not artificial intelligence in the sense we know today, but they laid the scientific groundwork upon which computer science was later built. From here began a long journey of research and development that eventually led humanity to the emergence of systems capable of learning, analysis, and decision-making, effectively starting the rise of artificial intelligence that changed the shape of the world.

What is the history of artificial intelligence? From a philosophical dream to a science that changed the world

Despite previous ideas and theories, the official beginning of the rise of artificial intelligence dates back to 1956, when a number of researchers and scientists met at the Dartmouth Conference in the United States, which is considered the most prominent event in the history of this field.

During this conference, American computer scientist John McCarthy coined the term “Artificial Intelligence” for the first time, becoming the official name for the science that seeks to develop systems capable of mimicking certain aspects of human intelligence.

At that time, researchers were extremely optimistic, believing that building machines with capabilities similar to the human mind could be achieved within a few years. Although reality proved the path was more complex than they expected, this conference represented the major turning point from which artificial intelligence research launched into the world.

From that moment, the evolution of AI began to accelerate through successive stages, starting from simple rule-based programs, expert systems, and machine learning, to deep learning and generative artificial intelligence technologies that are now capable of creating text and images, analyzing data, and making complex decisions with unprecedented accuracy.

This is why the Dartmouth Conference is viewed as the moment when artificial intelligence moved from being a mere theoretical idea to one of the most important and influential branches of modern technology in various aspects of life and business.

Stages of AI evolution over time: The milestones that created the modern technology revolution

As we mentioned, artificial intelligence has a long history, and its current capabilities did not happen overnight. It went through a long journey of successes, challenges, and technical developments that spanned decades. Here are the most important stages of AI evolution that shaped the history of this field and changed the future of technology:

1- Theoretical beginnings and the era of early optimism (1950 – 1970)

The 1950s witnessed the official launch of artificial intelligence after the term appeared for the first time during the Dartmouth Conference in 1956. During that period, there was a widespread belief among researchers that building a machine with mental capabilities similar to humans might be possible within a few years. During this phase, many early achievements emerged, most notably:

• Alan Turing proposed the Turing Test in 1950 to measure a machine’s ability to simulate human thinking.
• Development of the first programs capable of solving logical and mathematical problems.
• The emergence of the Logic Theorist program, considered one of the first artificial intelligence programs in history.
• Introduction of the concept of Machine Learning by Arthur Samuel in 1959.
• Development of early systems for games and logical inference.

Despite the limited technical capabilities at the time, this period laid the scientific foundations upon which the field was later built.

2- The first AI winter (1970 – 1980)

By the end of the 1960s, real challenges began to appear for researchers. Computers did not have enough power to process complex problems, and the available data and algorithms were not mature enough to achieve the dreams promised to the world. This led to:

• Declining confidence from governments and investors.
• Reduction of research budgets.
• Cancellation of many ambitious projects.
• A noticeable slowdown in the pace of innovation.

This is why this period was called the “AI Winter” due to the stagnation that hit the sector after the first wave of optimism.

3- The era of expert systems and the return to the spotlight (1980 – 1990)

The 1980s witnessed a new revival for artificial intelligence thanks to the emergence of what is known as Expert Systems—programs based on knowledge rules derived from human experts in specific fields. The most prominent features of this phase were:

• Using artificial intelligence in medicine to diagnose diseases.
• Employing it in the financial sector and risk analysis.
• Its entry into the fields of industry, management, and decision-making.
• Increased commercial investment in artificial intelligence technologies.

Expert systems proved that AI could provide real practical value within institutions and companies.

4- The second AI winter (late 1980s – 1990s)

But why did interest in the field decline again? Despite the success of expert systems, they faced a set of obstacles that limited their ability to evolve, most notably:

• High development and maintenance costs.
• Difficulty in constantly updating knowledge bases.
• Lack of self-learning capability.
• Complete reliance on pre-programmed information.

With the expected return on investment declining compared to the scale of investment, the field entered a new period of stagnation known as the second AI winter. However, behind this decline, the features of a greater revolution were silently taking shape.

5- The big data revolution and the beginning of the real transformation (2000 – 2010)

With the global spread of the internet and the emergence of smartphones and cloud storage, the world began producing massive amounts of data daily. This is where the most important shift in the history of artificial intelligence occurred. Instead of relying on fixed rules, systems became capable of learning from data and discovering patterns and relationships automatically. Key factors contributing to this shift included:

• Widespread internet adoption.
• Advancement in computer processor capabilities.
• Emergence of cloud computing technologies.
• Availability of Big Data.
• Development of databases and analysis tools.

This phase paved the way for the emergence of more advanced technologies such as machine learning and deep learning.

6- The era of deep learning and technical explosion (2010 – 2020)

Deep Learning is considered one of the most important turning points in the history of modern artificial intelligence. This approach relies on multi-layered neural networks that can process massive amounts of data and extract complex patterns from them. During this phase, AI achieved unprecedented achievements, including:

• High-accuracy image recognition.
• More advanced human language understanding.
• Instant machine translation.
• Smart voice assistants like Siri and Google Assistant.
• Development of self-driving cars.
• The AlphaGo program defeating world champions in the game of Go.

During this period, it became a practical part of the daily lives of millions of people around the world.

7- The era of generative artificial intelligence (2020 – present)

This phase represents the latest and most influential chapter of AI evolution so far. After years of focusing on analysis and prediction, modern systems have become capable of creating entirely new content based on human prompts. Applications of generative artificial intelligence include:

• Writing articles and texts.
• Producing images and designs.
• Creating videos.
• Developing programming code.
• Composing music and creative content.
• Building advanced digital assistants.

During this period, large language models and smart tools emerged, causing a radical shift in the sectors of education, business, marketing, and digital production, starting a new phase that may be the most influential in the history of artificial intelligence since its inception.

History of Machine Learning: How did machines learn to learn?

The history of Machine Learning is considered one of the most important chapters in the journey of artificial intelligence evolution, and it can even be considered the point that changed the rules of the game entirely. Before the emergence of machine learning, intelligent systems relied on fixed commands and rules set by programmers in advance, which made their capabilities limited in dealing with new situations.

With the advent of machine learning, computers became capable of acquiring knowledge from data and improving their performance over time without the need to be reprogrammed each time. The idea actually began in the 1950s when researchers proposed the concept of building systems that could learn from experience.

In 1959, Arthur Samuel coined the term Machine Learning while developing a program capable of improving its performance in the game of checkers the more it played. Over the years, the field witnessed rapid developments, represented by:

• The emergence of the first learning algorithms capable of discovering patterns and making predictions.
• Development of artificial neural networks inspired by the way the human brain works.
• Leveraging Big Data to train models on massive amounts of information.
• The emergence of Deep Learning, which enabled systems to make unprecedented leaps in understanding images, language, and sound.

If you want to understand how the world moved from traditional machines to systems capable of learning and decision-making, start by learning what artificial intelligence is, because understanding the present always begins with knowing the history that created it.

Most frequently asked questions about the history of artificial intelligence

When did the rise of artificial intelligence begin?

The official beginnings of artificial intelligence started in the mid-20th century, specifically in 1956 during the Dartmouth Conference, where the term was used officially for the first time.

Who is the founder of artificial intelligence?

It is not attributed to just one person, but John McCarthy is considered one of the most prominent names associated with its rise because he officially coined the term, alongside contributions from other scientists such as Alan Turing.

What are the most important stages of AI evolution?

Artificial intelligence has gone through several important stages, starting with the era of early optimism, then passing through periods of decline, before returning strongly with expert systems, then big data, then deep learning, leading to artificial intelligence generative AI.

What is the relationship between the history of Machine Learning and artificial intelligence?

Machine learning is one of the most important branches within artificial intelligence, and it is what gave machines the ability to learn from data and evolve over time instead of relying only on programmed commands.

What is the reason for the periods of decline in the evolution of artificial intelligence?

Periods of decline occurred due to the limitations of computers at those times, lack of data, high costs, and the fact that results were not always at the level of the high expectations that scientists aspired to.

How did artificial intelligence evolve to reach its current form?

It evolved thanks to the accumulation of scientific research, increased computing power, the emergence of the internet, the availability of big data, and then the entry of deep learning and generative AI, making it an essential part of our daily lives.

The future has begun, so are you ready for what is coming?

Now that you know that artificial intelligence is no longer just an emerging technology or an idea from science fiction movies, but has become a real force reshaping the way the world works and opening new paths in various fields, with innovations accelerating day by day.

Understanding the history of artificial intelligence is no longer just general knowledge, but an essential step to comprehending the major shifts that will affect business, education, the economy, and daily life in the coming years. Every stage of its evolution carries an important lesson about how bold ideas turn into a reality that changes the future.