The Evolution of Artificial Intelligence: From Enigma Code to the era of Generative AI

The history of artificial intelligence is marked by milestones that transformed not only technology but also the way we interact with machines.

It all began in the 1940s when Alan Turing led the decryption of the Enigma code during World War II. This was the first major step toward what we now understand as computational thinking and automated intelligence.

Decades later, after a long period of slow progress and lack of investment known as the "AI winter," IBM revolutionized the field with a moment that would change everything.

Deep Blue vs. Garry Kasparov: The Moment That Changed History

In May 1997, the world witnessed an unprecedented event: a machine defeated a world chess champion for the first time in an official series. The protagonist was Deep Blue, the supercomputer developed by IBM, which defeated Russian grandmaster Garry Kasparov, considered one of the greatest chess players of all time.

The series consisted of six games. Deep Blue won two, Kasparov won one, and they drew three. The decisive victory came in the sixth game, when Deep Blue played with an aggression that even made Kasparov think the machine must have received human assistance.

What was revolutionary was that Deep Blue did not use machine learning like modern AIs; it used raw computational power, evaluating up to 200 million positions per second, based on a vast database of historical games and advanced heuristics.

This event was a turning point: for the first time, a machine defeated human intellect in a domain considered the pinnacle of logic and strategic reasoning.

Deep Blue demonstrated that machines could surpass humans in specific domains, paving the way for new generations of intelligent systems like Blue Gene, Watson, and more recently Watsonx.

From Deep Blue to Blue Gene

From Deep Blue came a new vision: not just machines that play, but machines that help solve real-world problems. Thus, the Blue Gene project was born, an initiative that propelled supercomputing to unprecedented levels.

Unlike Deep Blue, designed for a specific task, Blue Gene was conceived to investigate topics such as:

• Molecular biology
• Protein simulation
• Disease modeling

Blue Gene not only elevated processing power, but it also paved the way for something even more ambitious: IBM Watson.

The Birth of Watson

In 2011, Watson surprised the world by defeating human champions of the program Jeopardy!. This time, not with raw computational power, but with something much more human:

• Natural language understanding
• Semantic analysis
• Interpretation of ambiguous questions and cultural references

Watson represented the birth of cognitive AI.

Subsequently, Watson adapted to industries such as healthcare, banking, and government, helping with complex decision-making, unstructured data analysis, and improving customer service.

The Era of Generative AI and the Arrival of Watsonx

Today, we live in a new era: that of Generative AI and foundational models. In this context, IBM launches Watsonx, a business platform designed to create, scale, and govern artificial intelligence solutions in a responsible and efficient manner.

What is Watsonx?

Watsonx is a suite that combines:

• watsonx.ai: the study of foundational models and generative AI development.
• watsonx.data: a data platform prepared for AI, optimized for analytics and governance.
• watsonx.governance: tools to govern the use of AI models, focused on compliance and trust.

IBM Watsonx Assistant

Within this evolution, Watsonx Assistant stands out, an enterprise solution that allows the creation of virtual assistants and intelligent chatbots with advanced natural language understanding and response capabilities.

Watsonx Assistant allows:

• Multichannel conversation integration (web, mobile, messaging, voice).
• Training with specific business data.
• Providing more natural, accurate, and contextualized experiences.
• Scaling securely under principles of privacy and traceability.

All this backed by models trained with business data, robust governance, and adaptability to multiple industries.

What Sets IBM Apart in the Current AI Era?

While many generative AI solutions focus on volume or generic creativity, IBM focuses on trust, traceability, and business utility.

Watson and Watsonx differ by:

• Explainability and transparency in models
• Training with reliable and auditable data
• Focus on specific sectors like healthcare, banking, and government
• Regulatory compliance and privacy protection
• Deep integration with real business workflows

Conclusion

From Enigma to Watsonx, through Deep Blue, Blue Gene, and Watson, the history of artificial intelligence is not just a line of code... it is a line of evolution.

An evolution that does not seek to replace humans, but to enhance their thinking, decisions, and creativity.

IBM’s AI has stopped being a promise for the future and has become a strategic ally for the present.