When people imagine machine learning, they tend to think about talking cars or humanoid robots–the stuff of sci-fi fantasy, or else dystopian fiction. But machine learning is neither, and it’s already changing what computers can do. In the near future anyway, it’s going to transform the way we work–starting with that smartphone in your pocket.

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Your smartphone is already portable and equipped with geolocation capabilities. Building off those features, it will soon be able to not just detect where you are but deliver what you need at that time and place better than any other device can. You’ll no longer need to search or wait for information–it will find you, then let you take action in ways you probably never thought possible on a handheld screen. So even if it isn’t that you’ll never be late or disorganized again, you’ll never have as good an excuse to be. With enough time, your smartphone might even learn how to get that hot cup of coffee delivered right to that 9 a.m. meeting. 2. Real Remote Work, Laptop-Free One day, we’ll look back at the workstation and the 9-to-5 work schedule and wonder how we got anything done. People travel more for work than ever before and have greater flexibility to work remotely. For better or worse, we’re “always on.” Products driven by machine learning will free us from having to choose between flexibility and productivity, from the C-suite all the way down. Voice transcription, powered by deep learning on neural networks, will fix your grammatical errors more accurately than ever on the fly. In fact, they’ll soon let you do business entirely by speech–no need for a sprawling keyboard or even a screen. Related improvements in input capabilities across all your devices will continue to make everything simpler, from setting up meetings and preparing presentations to organizing files and posting job ads. Even if it isn’t that you’ll never be late or disorganized again, you’ll never have as good an excuse to be. And let’s not forget email. Right now, it’s pretty annoying to send lengthy responses on a small screen, but what if software could automatically sort and highlight your most important messages, then predict and generate responses for you? Some of this is already possible today; further advances will let you be even more responsive and stay connected without tethering you so closely to a rectangular slice of glass. 3. Crunch Those Numbers For You You use your smartphone to figure out the tip on your brunch bill and divide it up based on who ordered the extra Bloody Mary. But tomorrow, we’ll use our mobile devices to perform much more complicated, high-value computations. Machine learning will make it easier to process and organize external information for work–whether that’s closing sales, generating reports, or changing your marketing budget in real time, from any device.

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As machine learning unlocks valuable skills such as data analysis and makes them available to anyone, smartphones will be an order of magnitude more powerful for those closest to any business challenge. Your phone will become a much more efficient and decisive problem solver. Smartphones will be an order of magnitude more powerful for those closest to any business challenge. Machine learning isn’t science fiction–it’s already here, in many products and features available today. And while there’s plenty of work still to be done–and no shortage of skeptics–the direction we’re heading in is pretty clear. The software and apps of the future promise to keep assignments from falling through the cracks, let us work from just about anywhere, and make better decisions with the aid of analyzed data. These changes will be gradual, and not every new development will succeed perfectly at first, but their cumulative effect on how we work will be profound, particularly on mobile. Machine learning is about to have its defining moment. Once it does, there’s no going back. Rich Rao leads the global Android, Chrome, and education businesses within Google for Work. He’s passionate about Google’s efforts to transform how we learn and work. Related: What’s The Future Of Innovation?