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Unraveling the History of AI: From the Dawn to the Present

AI Through the Ages: From Turing Tests to Trillion-Parameter Models

A Brief History of AI

Hello everyone. This is Jon. Today, I'll be talking about a brief history of AI (artificial intelligence). AI is gaining attention as a technology that will dramatically change our lives, but its origins are actually quite ancient. Research into AI began in the 1950s and has now evolved into familiar tools like ChatGPT. In this article, I'll trace the history of AI chronologically and provide an easy-to-understand explanation, including the latest trends as of 2025. I'll also provide simple explanations of technical terms so that even beginners can enjoy the article.

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The Beginnings of AI: The 1950s and 1960s

The history of AI dates back to the 1950s. First, in 1950, British mathematician Alan Turing proposed the "Turing test." This was a method for testing whether a machine could think like a human, and became the foundational concept of AI. The Turing test is a test that considers a machine to be "intelligent" if it can hold a conversation so natural that it is indistinguishable from a human.

In 1956, the Dartmouth Conference was held in the United States, where the term "artificial intelligence (AI)" was officially coined. This conference is known as the starting point of AI research. Researchers at the time believed that computers could solve problems like humans, and made optimistic predictions. For example, it was said that within 10 years, an AI would be created that could beat the world chess champion.

The first AI programs appeared in the 1960s. ELIZA, developed in 1966, was a chatbot capable of simple conversations that mimicked psychotherapy. This was an early example of AI. However, computers at the time were less powerful, and advances in AI were slower than expected.

AI Winter and Revival: 1970s to 1990s

In the 1970s, AI research entered a period of stagnation known as the "AI winter." This was a time when research progressed slowly due to a lack of funding and technological limitations. For example, in 1973, the UK's Lighthill Report pointed out the limitations of AI, leading to funding cuts. The AI ​​winter is a cycle in which expectations are over-inflated, leading to widespread disappointment and research stagnation.

However, there were signs of a revival in the 1980s. Research into neural networks (learning models that mimic the nerve cells of the brain) progressed, and expert systems (systems that incorporate expert knowledge into AI) emerged. In Japan, too, the Fifth Generation Computer Project was underway, sparking an AI boom.

The 1990s saw significant progress. In 1997, IBM's Deep Blue defeated the world chess champion Garry Kasparov, demonstrating that AI could surpass humans in certain areas. The foundations of machine learning (the ability to automatically learn from data) also began to take shape, laying the foundation for a later boom.

  • 1970s: AI winter begins, funding cuts.
  • 1980s: The resurgence of neural networks.
  • 1997: Deep Blue beats a human at chess.

The era of deep learning: 2000s to 2010s

AI evolved rapidly in the 2000s, driven by the spread of the internet and the increase in big data (massive amounts of data). Deep learning (an advanced form of neural network) gained attention in 2006, dramatically improving the accuracy of image and voice recognition. Deep learning is a technology that processes data at multiple layers to learn complex patterns.

In 2012, an AI called AlexNet achieved human-level image recognition in the ImageNet competition, sparking an AI boom. Around this time, companies like Google and Facebook (now Meta) began investing huge amounts of money in AI research.

In the late 2010s, AI began to become more prevalent in everyday life. In 2016, AlphaGo defeated the world champion of Go, demonstrating the potential of AI to the world. AlphaGo is an AI that combines deep learning and reinforcement learning (a method of learning through trial and error). In addition, a model called Transformer appeared in 2017 and became the foundation of natural language processing (technology for understanding text). This later led to ChatGPT.

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The Modern AI Boom and the Latest Trends in 2025

AI has exploded in popularity since the 2020s. In 2022, OpenAI's ChatGPT was released, making it easy for anyone to converse with AI. ChatGPT is a large-scale language model (LLM, an AI trained with large amounts of text data) based on the Transformer. This has established AI as a tool for business and education.

As of 2025, the evolution of AI shows no signs of stopping. The latest information is that DeepSeek released DeepSeek-R1 on January 20, 2025. This is a model that uses a chain of thought (a method of solving problems step by step) and exhibits performance comparable to OpenAI models in mathematical and programming tasks. It is open source (anyone can use it for free), and has become a hot topic.

Additionally, on January 21, US President Donald Trump officially announced the Stargate Project, a joint project between OpenAI, SoftBank, Oracle, and MGX, which aims to strengthen AI infrastructure. Furthermore, on January 23, a benchmark called Humanity's Last Exam was released, which includes over 3,000 difficult questions to measure AI capabilities.

On X (formerly Twitter), AI trends for 2025 include predictions of the achievement of AGI (artificial general intelligence, human-level general AI) and the release of new models such as Claude 4, Gemini 3, and GPT-5. Additionally, Microsoft's AI updates include the announcement of a next-generation AI chip using microfluidic cooling technology and new features for Copilot, furthering the automation of business processes. X's posts suggest that 2025 will be the year in which AI will improve its problem-solving capabilities as a "reasoner" and advance tool integration.

  • January 20, 2025: DeepSeek-R1 release (open source LLM).
  • January 21, 2025: Stargate Project announced.
  • Latest trends for 2025: Diverse model releases and the rise of agent AI (automated agents).

Jon's Summary

Looking back at the history of AI, it began as a dream in the 1950s, overcame several hardships, and has now evolved to the astonishing extent it is today. In 2025 in particular, open-source models and large-scale projects like DeepSeek-R1 are likely to make AI even more accessible. AI will continue to change our lives, but we must be mindful of its ethical use. I encourage you to try out new ideas using AI.

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