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Take a stroll along the AI timeline
The introduction of AI in the 1950s very much paralleled the beginnings of the Atomic Age. Though their evolutionary paths have differed, both technologies are viewed as posing an existential threat to humanity. -
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The history of artificial intelligence: Complete AI timeline
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1950
Alan Turing published "Computing Machinery and Intelligence," introducing the Turing test and opening the doors to what would be known as AI. -
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The history of artificial intelligence: Complete AI timeline
From the Turing test's introduction to ChatGPT's celebrated launch, AI's historical milestones have forever altered the lifestyles of consumers and operations of businesses. -
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1951
Marvin Minsky and Dean Edmonds developed the first artificial neural network (ANN) called SNARC using 3,000 vacuum tubes to simulate a network of 40 neurons. -
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1952
Arthur Samuel developed Samuel Checkers-Playing Program, the world's first program to play games that was self-learning. -
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1956
Arthur Samuel developed Samuel Checkers-Playing Program, the world's first program to play games that was self-learning. -
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1958
Frank Rosenblatt developed the perceptron, an early ANN that could learn from data and became the foundation for modern neural networks. John McCarthy developed the programming language Lisp, which was quickly adopted by the AI industry and gained enormous popularity among developers. -
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1959
Arthur Samuel coined the term machine learning in a seminal paper explaining that the computer could be programmed to outplay its programmer. Oliver Selfridge published "Pandemonium: A Paradigm for Learning," a landmark contribution to machine learning that described a model that could adaptively improve itself to find patterns in events. -
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1964
Daniel Bobrow developed STUDENT, an early natural language processing (NLP) program designed to solve algebra word problems, while he was a doctoral candidate at MIT. -
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1965
Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg and Carl Djerassi developed the first expert system, Dendral, which assisted organic chemists in identifying unknown organic molecules.
The evolution of chatbots from Eliza to Bard. -
Big data's great equalizer
AI can be considered big data's great equalizer in collecting, analyzing, democratizing and monetizing information. The deluge of data we generate daily is essential to training and improving AI systems for tasks such as automating processes more efficiently, producing more reliable predictive outcomes and providing greater network security. -
Artificial intelligence
Artificial intelligence, or at least the modern concept of it, has been with us for several decades, but only in the recent past has AI captured the collective psyche of everyday business and society. -
The ability of computers and systems to perform tasks
AI is about the ability of computers and systems to perform tasks that typically require human cognition. Our relationship with AI is symbiotic. Its tentacles reach into every aspect of our lives and livelihoods, from early detections and better treatments for cancer patients to new revenue streams and smoother operations for businesses of all shapes and sizes.