The history of artificial intelligence is a surprisingly long one! The following outlines some of the highlights of this evolution, including key studies and experiments and the fits and starts of the multiple “AI Winters” along the way.

Understanding a bit about the work that preceded recent developments just underlines how extraordinary the Cambrian-like explosion of GenAI-related advancements truly is.

<aside> 💡 Make sure to explore the included links we’ve provided for more insight!

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1950’s - The Birth of AI

• 1950: Alan Turing introduces the Turing Test in his paper "Computing Machinery and Intelligence."
• 1956: The Dartmouth Workshop takes place, often considered the birth of AI as a field.

1960’s - Early Progress & Expert Systems

• Researchers focus on symbolic AI and rule-based systems.
• The first chatbot, ELIZA, was created at MIT in 1966. You can try a conversation with ELIZA here.

1970’s - The First AI Winter

• Funding and interest in AI drop due to the limitations of rule-based systems and unmet optimistic predictions.

1980’s - Revival with Expert Systems

• Commercialization of AI with the advent of expert systems.
• The backpropagation algorithm for training neural networks is popularized, setting the stage for deep learning.

Bee Partner Tim Smith’s 1988 article on AI in the U.C. Berkeley School of Business Cal Business Weekly

1990’s - Machine Learning Gains Traction

• Development of algorithms like Support Vector Machines (SVM).
• Reinforcement Learning is formalized and gains popularity with algorithms like Q-learning.

2000’s - The Rise of Data

• Increased data collection and computing power lead to advancements.

• In 2012, Deep Learning came to the forefront with AlexNet, a deep neural network that won the ImageNet competition, showing the potential of deep learning in Computer Vision.

  

  Images from ImageNet used for training computer vision models