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Did you know? Machine learning's roots go back to Alan Turing's 1940s concept of a universal learning machine! Coined by Arthur Samuel in 1959, it's more than just a digital age buzzword—it's a deep dive into the history of computing. #CortouchMedia #MachineLearningHistory #TechEvolution #TGIF #FridayFeeling #WeekendVibes #TechInnovation #DigitalRevolution #AIHistory #LearnFromThePast #Ibadantechcommunity #Lagostechcommunity #3MTTLearningCommunity

Unlike some humans, ChatGPT does not take credit for the work of others and provides factual information as to who, where and when it invented back propagation. #machinelearninghistory

Unlike some humans, ChatGPT does not take credit for the work of others and provides factual information as to who, where and when it invented support vector machines #machinelearninghistory

2016 – Google’s artificial intelligence algorithm beats a professional player at the Chinese board game Go. The AlphaGo algorithm developed by Google @DeepMindAI managed to win four games out of five in the Go competition. #MachineLearningHistory

2015 – Over 3,000 AI and Robotics researchers, endorsed by Stephen Hawking, Elon Musk and Steve Wozniak (among many others), sign an open letter warning of the danger of autonomous weapons which select and engage targets without human intervention. #MachineLearningHistory

2015 – @Microsoft creates the Distributed #MachineLearning Toolkit, which enables the efficient distribution of machine learning problems across multiple computers. #MachineLearningHistory

2015 – @amazon launches its own machine learning platform. #MachineLearningHistory

2014 – @facebook  develops DeepFace, a software algorithm that is able to recognize or verify individuals on photos to the same level as humans can. #MachineLearningHistory

2012 – Google’s X Lab develops a #MachineLearning algorithm that is able to autonomously browse @YouTube videos to identify the videos that contain cats. #MachineLearningHistory

2011 — @GoogleBrain is developed, and its deep neural network can learn to discover and categorize objects much the way a cat does. #MachineLearningHistory

2011 — IBM’s Watson beats its human competitors at Jeopardy. #MachineLearningHistory

2010 — The @Microsoft Kinect can track 20 human features at a rate of 30 times per second, allowing people to interact with the computer via movements and gestures. #MachineLearningHistory

2006 — Geoffrey Hinton coins the term #DeepLearning to explain new algorithms that let computers “see” and distinguish objects and text in images and videos. #MachineLearningHistory

1997 — IBM’s Deep Blue beats the world champion at chess. #MachineLearningHistory

1990s — Work on #MachineLearning shifts from a knowledge-driven approach to a data-driven approach.  Scientists begin creating programs for computers to analyze large amounts of #data and draw conclusions — or “learn” — from the results #MachineLearningHistory

1985 — Terry Sejnowski invents NetTalk, which learns to pronounce words the same way a baby does. #MachineLearningHistory

1981 — Gerald Dejong introduces the concept of Explanation Based Learning (EBL), in which a computer analyses training #data and creates a general rule it can follow by discarding unimportant data. #MachineLearningHistory

1979 — Students at Stanford University invent the “Stanford Cart” which can navigate obstacles in a room on its own. #MachineLearningHistory

1967 —The nearest neighbor algorithm was written, allowing computers to begin using very basic pattern recognition. This could be used to map a route for traveling salesmen, starting at a random city but ensuring they visit all cities during a short tour. #MachineLearningHistory