Quick Draw, the self learning, doodle identifying technology is starting to sweep the internet with its very amusing and enjoyable qualities. So, to help the people know more about them, Google has collected some interesting demos and placed them at its Google AI Experiments showcase.
The game is as simple as you can imagine - at least in theory - as the player is presented with a series of words and they are then asked to draw a representation of that image in under 20 seconds. But the more you play with it, the more it will learn. To this end, Google has collected a number of demonstrations for machine learning that people can interact and play with. Experiments, where anyone from hobbyist to professional level can explore experiments created using Google CloudVision API and TensorFlow and use the tools to create their own applications. At the start, we pioneered large-scale statistical machine translation, which uses statistical models to translate text. One can also map to explore neighborhoods of similar sounds.
Usually, translated sentences are not always flawless, but they get close enough to be understandable for the native speaker.More news: Dominic Thiem outguns Gael Monfils, earns point in London
The company also announced it would be opening up its Neural Machine Translation API to developers and businesses through the Google Cloud. As you open the AI Experiment page, you'll see different experiments. However, don't expect it to spew out the correct outcome every time as the neural network has now been trained to recognize only over a 100 different concepts. The plan is to implement all remaining forms of communication that you can find in Translate. It uses machine learning to understand how job titles and skills relate to one another and what job content, location, and seniority are the closest match to a jobseeker's preferences.
Visualizing High-Dimensional Space: It helps use to visualize what's happening in the machine learning and also allow coders to use and explore their high-dimensional data. If you're on point, however, the neural network will hone in on the object and guess correctly.
Neutral Networks: In this experiment, you can turn on your camera to explore how each layer of the neutral works.