I'm not much of a sketcher or drawer, but 'Quick, Draw!' is definitely inspiring me to bring out my inner artist. How Google 'Quick, Draw!' works is pretty fascinating the Pictionary-like game relies on machine learning to guess what it is you're drawing. Now, the tech giant has released a new artificial intelligence (AI) experiment called 'Quick, Draw!' that anyone can play.

Given that neural networks help the apps improve over time by learning, their use can substantially improve user's experience.Google is known for being at the forefront of technological innovation, from its daily animated doodles to its virtual reality headset, Google Cardboard. Recently, companies like Microsoft and SwiftKey have showcased how neural networks can improve artificial intelligence used in their apps by the understanding of broader context. On the basis of our experience with the game, it can get really challenging and requires some thinking but never stops being fun. Notably, players get just 20 seconds to draw their doodles before the game provides them with a new word. Interested readers can check out the game over here.Įven though the function of Quick Draw seems simple at the surface, the use of neural networks ensures that the guesses, which are made in realtime, are accurate.

It tries to guess the word from the doodle being drawn by the player and if your doodle is not up to the mark, you don't get any points. Then the players have to draw the doodle using just their mouse cursor and then company's artificial intelligence gets into action. On Tuesday, the company announced the implementation of the technique for its translation tool and now its latest mini-game 'Quick Draw' showcases how this technology can be both impressive and fun at the same time.Īlthough the name of the web game suggests that it might have something to do with the Wild West, Quick Draw asks players to draw doodles of a certain word that is shown to them. Google seems to be currently obsessed with neural networks, which uses human-like systems to bring contextual understanding to machine learning.

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