History of Machine Learning
As days pass by, technology gets more and more advanced. The computers’ abilities to analyze and interact with the world is increasing at a remarkable rate.
But we often forget the history and focus vividly on the future. But understanding the history of Machine Learning can surely motivate you! I assure you, it won’t be like those boring history classes in school. All I’ll be doing is just present a short timeline of Machine Learning.
Timeline of Machine learning
1950- The “Turing Test” was created to determine if a computer has real intelligence. The test required the computer to fool a human into believing that it is also human.
1957- The Perceptron (the first neural network for computers) were created which simulate the thought processes of the human brain.
1967- The “nearest neighbor” algorithm was written, which allowed computers to recognize very basic patterns. A typical usage of this was to map a route for a salesman, ensuring they visit a given number of cities during a short tour.
1979- The “Stanford Cart” was invented by some students at Stanford University, which could navigate obstacles in a room all by itself.
1981- The concept of EBL (Explanation Based Learning) was introduced, in which a computer could analyze a given data and create a general rule by discarding unimportant data.
1985- NetTalk was invented, which could pronounce words, just like a baby does.
1990s- Work on Machine Learning shifted from a knowledge-driven approach to a data-driven approach, enabling computers to analyze or learn from large amounts of data.
1997- Deep Blue, created by IBM, beat the world chess champion, Garry Kasparov, under standard chess tournament time controls.
2006- Computers learned to “see” and distinguish objects and text in images and videos.
2010- The Microsoft Kinect could track 20 human features at a rate of 30 times per second, which allowed people to interact with the computers via movements and gestures.
2011- Again, IBM’s Watson, defeated its human competitors at Jeopardy!.
Same year, Google Brain was developed which could be used to discover and categorize objects.
2012- Google’s X lab developed an algorithm that could autonomously browse YouTube videos that contained cats.
2014- Facebook creates DeepFace, that could recognize/verify individuals on photos the same way humans can.
2015- Amazon launched its own Machine Learning platform
Microsoft created the Distributed Machine Learning Toolkit, which enabled the efficient distribution of machine learning problems across multiple computers.
Over 3000 AI and Robotics researchers signed an open letter warning of the danger of autonomous weapons.
2016- Google’s AI algorithm beat a professional player at the Chinese board game Go, which is the world’s most complex board game.
Even though Machine Learning can do so many similar things like humans, many scientists believe that they can never think in the same way humans do. What do you think about it? Will Machines surpass humans?