Artificial intelligence (AI) seems to be everywhere. A massive number of companies, both inside and outside the tech world, are using AI to help improve their businesses or offer new products.
While the tech has only really seen mainstream use in just the past decade, researchers have been trying to create artificial intelligence — machines that can think like a person does — for decades.
The origins of modern AI can be traced back as far back as the 1950s — and the concept behind the tech is even older than that.
This is where AI tech has come from — and where it’s probably going.
AI’s Early History
In the mid-20th century, research computers were slowly becoming cheaper and more accessible. For the first time, it was possible for universities — even those without massive budgets — to afford computers that could store commands and information, allowing researchers to experiment with early computer programming.
As a result, a growing number of scientists became more and more interested in answering the same question — could you make a computer think?
The phrase “artificial intelligence” itself was first used at the Dartmouth Summer Research Project on Artificial Intelligence (DSRPAI) in 1956, organized by John McCarthy and Marvin Minsky.
The conference was key for the development of AI, and kicked off a multi-decade period of enthusiasm and investment in new AI techn. From the 1950s to the 1970s, there was significant research on early AI and a lot of optimism about what researchers would be able to achieve. In general, the feeling was that, within a generation, there would be computers that were just as intelligent and good at problem-solving as the average person.
Developing the Tech Behind Modern AI
Early versions of modern AI tech would emerge later.
The 80s and 90s saw the foundation laid for a lot of the practical AI tech that you encounter in your daily life.
For example, neural networks are a popular modern AI tech that’s used to power AI advancements like computer vision — which allows a computer to “see,” breaking down complex visual input into objects and shapes. Much of the groundwork for modern neural networks was developed in the mid-1980s.
By the 1990s, researchers were starting to demonstrate how AI that used a particular kind of algorithm to learn, called backpropagation, were able to beat professional players in games like backgammon, checkers and chess.
The 90s also saw a number of other major AI advancements — like a cross-U.S. tour of the first semi-autonomous car, powered by AI.
Modern Uses of AI
Today, AI is almost anywhere. If you regularly use the internet, you’re probably taking advantage of some type of modern AI.
Most major names in tech — like Alphabet, Microsoft, Amazon and Apple — use AI in one way or another. New product recommendations algorithms, modern search engines and many customer service chatbots are all examples of AI in practice.
The influence of AI extends well beyond the tech world. AI-powered warehouse robots help workers organize goods, self-driving cars are now just a few years or more from being a reality. In just about every field, AI data analysis can help improve predictions and analyze unstructured data. The right tool can also help data analysts find subtle patterns that you might not be able to find with a more traditional analytic approach.
Theoretical AI research is still ongoing. For many scientists, the goal remains more and more complex AIs. The most ambitious researchers hope to eventually develop AIs that have a theory of mind — or even self-awareness. However, this kind of AI is closer to science fiction than something you’ll probably see in the near future.
What’s Next: The Future of AI
AI tech, more than 70 years in the making, is still advancing. In the near future, researchers hope to use AI to power completely self-driving cars, advanced machine translation tools and new autonomous robots for manufacturing and construction.
Beyond that, scientists are still pursuing the original goal of AI research — creating machines that think in the same way that people do. This tech is probably still a very long way off. Less complex AI, however, is likely to become increasingly important to business and daily life.
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