The AI Evolution is a fascinating tale of transformation, from a quirky novelty to a powerful force shaping our world. Once the stuff of science fiction, AI has become a reality, thanks to the  computer technology of the twentieth-first century. Surprisingly for decades, AI remained largely within the research community, but now it’s transforming our lives. Indeed, advances in computer processing, high-speed internet, and affordable data storage have given AI the power to access vast data sets and redefine industries. Now, AI is pushing the boundaries of what is possible. In this article, I’ll provide you a short history of this AI Evolution.

The Prelude to the AI Evolution: Myths, Novelty Automation and Mathematics

The idea of artificial intelligence has roots in ancient myths and early philosophical musings, where creating intelligent machines was more fantasy than reality. During this time, inventions like the Mechanical Turk, a chess-playing machine built in 1770, gave the illusion of AI. Amazingly, the Turk, which hid a human player inside, fooled the public for 84 years and defeated notable figures like Napoleon Bonaparte and Benjamin Franklin. Despite its deception, it inspired many. Meanwhile, scholars’ advancements in logic and formal reasoning ultimately led to the invention of the programmable digital computer in the 1940s.

“Artificial Intelligence (AI) is the science of how to get machines to do the things they do in the movies.”

Astro Teller

1950s – From Theory to Digital Computers.

In the second half of the twentieth century, computer technology became a reality. Also, this is when the idea of artificial intelligence transitioned from a theory to something real and tangible. In 1950, Alan Turing (famous for breaking the Nazis’ Enigma code) published the groundbreaking paper, “Computing Machinery and Intelligence”. In this book Turing proposed to answer the question “can machines think?” and he introduced the Turing Test. Specifically, he designed his Turing test to determine if a computer could demonstrate the same intelligence as a human. Also during this period, pioneers like Claude Shannon and Marvin Minsky furthered the advancement of computers and explored the potential of machines to mimic human intelligence.

“can machines think?”

Alan Turing

1980 – 1990s – The AI Evolution of Expert Systems that Simulates Human Knowledge.

In the following decades AI research and development continued, but at first AI developers did not have much success at commercializing their AI software. Again, to the general public AI was considered a novelty. As an example, what the public saw in AI was limited to such things as computer chess games that had limited entertainment value.

Finally in the early 1980s, AI research was revived by the commercial success of expert systems. Specifically, these AI software programs simulated the knowledge and analytical skills of human experts. Consequently, by 1985 the market for AI had reached over a billion dollars. However, interest in AI soon waned, and what became to be known as the “AI winter” began for several decades. This was because there was a large gap between AI expectations and its actual capabilities.

2000 to 2020 – Revolutionary Deep Learning AI Powered by Fast, Cloud Computing.

The new millennium saw a seismic shift in AI, driven by the advent of deep learning and the availability of powerful cloud computing resources. Deep learning, a subset of machine learning, enabled AI systems to learn from vast amounts of data and make predictions with unprecedented accuracy.

Now, AI could move from the research lab and transform into a commercially viable industry. For instance, cell phone users started using Apple’s virtual assistant, Siri,  with its natural language interface. Additionally, Google’s Jeff Dean and Andrew Ng started using neural networks and deep learning. In this case, this AI could learn and recognize patterns in order to label millions of images. Over the next couple of decades, behind the scenes from the general public, AI and machine learning (ML) continued to advance.

2020 and Beyond: AI Explodes with Large Language Models, Autonomous Agents, and Advanced Robotics.

In January 2023, OpenAI’s ChatGPT became the fastest-growing consumer software application in history, gaining over 102 million users in two months. The tech behind ChatGPT was a cumulation of the latest advancements in generative AI models. This type of AI is capable of generating highly detailed images and human-like text. Per the chart below, generative AI continues to improve in mimicking human reasoning.  

Concurrently with the ChatGPT explosion, both autonomous AI agents and robotics were reaching breakthroughs in a wide range of use cases. To detail, autonomous agents, from self-driving cars to smart home devices, were becoming increasingly sophisticated, capable of navigating complex environments and making real-time decisions. Also, advanced robotics, powered by AI, are now transforming manufacturing, healthcare, and exploration, pushing the boundaries of what machines can achieve. 

“Artificial intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise, you’re going to be a dinosaur …”

Mark Cuban

References.

It is indeed amazing that AI software is now thought of as a consumer product. Moreover, business software vendors are incorporating AI into their offerings to perform a wide range of functions. This includes AI assistants, computer vision AI, smart robotics, recommendation engines, and decision platforms to name a few. For more AI business use cases, see my article, Here Are 9 Examples Of Artificial Intelligence (AI) Technology That Will Best Empower Supply Chains.

Also, below are more references on AI Evolution.

• Our World in Data’s Artificial Intelligence
• Wikipedia’s History of Artificial Intelligence
• Coursera’s The History of AI: A Timeline of Artificial Intelligence
• IBM’s History of Artificial Intelligence

Here Are 9 Examples Of Artificial Intelligence (AI) Technology That Will Best Empower Supply Chains

Need help with an innovative supply chain solution that leverages emerging information technologies? I’m Randy McClure, and I’ve spent many years helping logistics organizations to make the most of new information technologies. As a supply chain tech advisor, I’ve implemented hundreds of successful projects across all transportation modes, working with the data of thousands of shippers, carriers, and 3rd party logistics (3PL) providers. I specialize in new strategies, proof-of-concepts and operational pilot projects using emerging technologies and methodologies. If you’re ready to supercharge your supply chain or if you are a solution provider, let’s talk. To reach me, click here to access my contact form or you can find me on LinkedIn.

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