Emoji Scavenger Hunt is a game built using neural networks. Developed by Google using TensorFlow.js, a version of the machine learning library designed to run on browsers, the game showcases how machine learning can be brought to web applications. But more importantly, TensorFlow.js, which was announced at the end of March at the TensorFlow Developer Summit looks like it could be a tool to define the next few years of web development, making machine learning more accessible to JavaScript developers than ever before.
Start playing now.
At the moment Emoji Scavenger Hunt is pretty basic, but the central idea is pretty cool. When you open up the web page in your browser and click ‘Let’s Play’, the app asks for access to your camera. The game then starts: you’ll see a countdown, before your camera opens and the web application asks you to find an example of an emoji in the real world. If you find yourself easily irritated you’re probably not going to get addicted, as Google seem to have done their best to cultivate an emoji-esque mise en scene. But the game nevertheless highlights not only how neural networks work, but also, in the context of TensorFlow.js, how they might operate in a browser.
Of course, one of the reasons Emoji Scavenger Hunt is so basic is because a core part of the game is training the neural network. Presumably, as more people play it, the neural network will improve at ‘guessing’ what objects in the real world relate to which emoji on your keyboard.
What’s exciting is how TensorFlow.js might help shape the future of web development. It’s going to make it much easier for JavaScript developers to get started with machine learning – on Reddit a number of users were thankful that they could now use TensorFlow without touching a line of Python code. On the other hand – perhaps a little less likely – TensorFlow.js might lead to more machine learning developers using JavaScript. If games like Emoji Scavenger Hunt become the norm, engineers and data scientists will have a new way to train algorithms – getting users to do it for them.
Eagle-eyed readers who have been watching TensorFlow closely might be thinking here – what about deeplearn.js? Fortunately, the TensorFlow team have an answer: TensorFlow.js… is the successor to deeplearn.js, which is now called TensorFlow.js Core.
The announcement of TensorFlow.js highlights that Google and the core development team behind TensorFlow have a clear focus on the future. They’re already the definitive library for machine learning and deep learning. What this will do is spread its dominance into new domains. Emoji Scavenger Hunt is pointing the way – we’re sure to see plenty of machine learning imitators and innovators over the next few years.
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