The History of Artificial Intelligence

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The History of Artificial Intelligence

The History of Artificial IntelligenceAI is a hot field these days, and it has a really interesting history. If you ever wanted to learn more about the origins and evolutions of artificial intelligence as a field, then you’re in the right place, ’cause that’s the topic of this article. All right, so as I mentioned, AI has a really interesting history, which in some ways began in the 1930s and 40s when people were really interested in science fiction, and that’s the type of fiction that is focused on potential future advancements in both science and technology, things like alien life forms, time and space travel, and intelligent robots.

So in a previous article, I defined AI as simply intelligence exhibited by machines, and so intelligence is really just the idea of learning, understanding, and using that knowledge learned in order to achieve one or more goals or carry out tasks.

So in the case of humans, we use human intelligence regularly to perform tasks like having a conversation. In 1950, a mathematician named Alan Turing published his seminal paper called “Computing Machinery and Intelligence”, and in that paper, he introduced the famous Turing test, a test where he’s basically asking questions of can machines think like humans, or alternatively, can machines imitate a human in a test that now is famously known as the imitation game?

Following the Turing paper, the first AI programs were created in the early to mid 1950s, and they focused mainly on playing chess, checkers, and proving mathematical theorems. In 1956, Dartmouth College hosted the Dartmouth Summer Research Project on Artificial Intelligence, a workshop that is widely considered the birthplace of the field of artificial intelligence itself.

In fact, the event organizer, John McCarthy, a scientist at Dartmouth, coined the term AI around that time. The workshop included a gathering of scientists and mathematicians that brainstormed and discussed different ways that machines could potentially exhibit intelligence. In fact, many of the topics they discussed then are still very applicable to AI today, things like natural language processing and neural networks.

The mid to late 1950s and 1960s brought about additional advancements in AI, but also brought about unmet expectations, excessive hype, and overly optimistic predictions about the advancement of AI capabilities. This was followed by the first AI winter, a period where interest in funding in AI declined. But luckily things picked up again in the 1980s, and research, interest, and funding increased again in artificial intelligence, and that’s where we started to see the first so-called expert systems, or systems that are meant to mimic human experts in the way that they make decisions.

And we also saw the first autonomous vehicles from Carnegie Mellon University, called Navlab. Unfortunately, this was followed by another AI winter from the late 1980s through to the early 1990s. But despite this AI winter, two very pivotal things happened at that same time. The first was the birth of the Internet and the World Wide Web, which created an absolute explosion of data and data sharing. The second was a major shift from expert rules-based AI systems to predominantly beta-driven AI systems that used machine learning techniques to automatically learn from data without requiring explicit programming.

This area marks the beginning of the way that machine learning is used today. In the 1990s and early 2000s, the world saw Deep Blue, an AI program that beat the world reigning champion at chess, Garry Kasparov, and also the introduction of NaturallySpeaking, the first publicly available speech recognition system, created by Dragon Systems.

This was closely followed by Amazon’s Recommendations, and Geoffrey Hinton coining the term Deep Learning, which represents an advanced neural network-based area of artificial intelligence that’s really well suited for object detection, image classification, pattern recognition, machine translation, and natural language-related tasks.

The last 10 years have been characterized by an absolute explosion in data and computational ability, and also where we’ve seen some of the most famous examples of AI in the real world, things like IBM’s Watson beating the world champions at Jeopardy, Apple introducing Siri, machines seeing cats in images, and also AlphaGo, an AI powered system that was able to beat the world champion at the game Go, which is a extremely difficult game for humans.

And in the last few years, we’ve seen a major increase in the number of real world applications and use cases of AI, which means we’re really in the era of applied AI as opposed to theoretical or academic AI. In 2018, Google’s CEO said that AI may be one of the most important things that humanity is working on, and may be more profound than even electricity or fire.

AI will continue to have a significant impact on society and our lives All right, we’ve covered a lot, and hopefully that was a helpful journey through the history of artificial intelligence. Please let us know in the comments of any AI facts or developments that you think are important that I didn’t talk about today.

 

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reference – The History of Artificial Intelligence

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