SwiftKey launched its Neural Alpha keyboard in October of last year, and today — almost a year later — the company is introducing neural network-powered word predictions to its namesake main app. This means better word predictions and autocorrect, since the app now better understands the context of what you’re trying to say…
Google Brain, the search giant’s machine learning arm, is setting up a new group to see if it can teach AI to make its own, original works of art. The company, named Magenta, will be announced more officially at the beginning of June, but was referenced to in a talk given by Douglas Eck, a Google Brain researcher, at Moogfest.
You may remember a little while back it was revealed that Google has been feeding its neural networks steamy romance novels to read. The aim through this exercise was to teach it to produce more human-like responses in order to power its search results and ‘smart reply’ systems.
As well as forcing its neural networks to digest more than 11,000 unpublished books (3,000 of which were romance), Google Brain’s engineers have also been teaching it to relate two unique phrases to each other. As revealed in a Quartz article, the method was fairly straightforward and resulted in some really weird, romantic, dark ‘poetry’.
Over the past couple of years, Google has been implementing a number of AI, or machine-learning technologies, in to its products. Whether it’s intuitive search within the Photos app, better automatic thumbnail creation in YouTube, ‘Smart Reply’ in Inbox, or just straight-out beating an 18-time Go world champion, its artificial intelligent brains are being developed and honed.
With all of its incredible talent, apparently, there’s still work to be done when it comes to results from neural networks sounding and looking like naturally spoken or written human language. The solution: feeding it steamy romance…
Back when I was in high school, I remember our computer studies teacher telling us that a computer only does what it’s told to do, and so mistakes are not the machine’s, but rather the user’s. With neural networks and machine learning, that is no longer true. AlphaGo, DeepMind’s specialist Go-playing machine, has proved as much. AlphaGo has been programmed to learn from its mistakes, and can err all on its own.
The AI-powered system failed to recover from an error against Lee Sedol in their fourth game, and eventually lost. In the fifth game, however, it made a mistake and was able to win the series in seemingly dramatic fashion.
People on the Internet have long been captivated by the artwork made by Google’s neural networks. While created by a computer, many have called it dreamlike and surreal. The company realizes the artistic implications of machine learning and is starting a program that brings together artists and engineers to make new works.
Google has trained a neural network, named PlaNet, to figure out where an image was taken down to the city and even exact street level. The machine only needs to analyze a photo’s pixels in order to accomplish the task.
Google hasn’t been shy about sharing how it uses advanced neural networks (informally known as AI) in some of its products. The company has been teaching its machine learning tools a slew of new tricks in recent months. Google Photos uses it to easily find specific images based on your search, they equipped YouTube with the ability to better select thumbnails, reply to your emails from Gmail and made Google Translate far better at reading signs. And now, it wants to share its machine learning engine with developers, to make it even better…
Update: It looks like the Smart Reply feature is rolling out starting tomorrow.
To all those asking, Smart Reply will start rolling out to Inbox on Android and iOS tomorrow.
— Inbox by Gmail (@inboxbygmail) November 4, 2015
Google’s Inbox app for Gmail is one of the best things to happen to personal email management since email was invented. Using Google Now’s power, it can automatically create calendar events, sort out your junk and priority emails and suggest reminders. Now it’s about to get a whole lot smarter…
Photo: chromespot.com
When Google announced (and later began rolling out) conversational search back in May, the company saw that as only the start. The company’s plans for the feature take us all the way into the realms of a true virtual personal assistant.
If you haven’t yet tried conversational search in Chrome, the feature as it stands is useful but basic. Speak a search like “How old is Barack Obama?” and Chrome will speak the answer. With a person, you could then ask a series of follow-up questions like “How tall is he?”, “Who is his wife?” and “How old is she?” and they would know who you were referring to in each question. That’s the functionality Google is rolling out, remembering who or what you just asked about and interpreting pronouns appropriately.
But Google’s long-term plans are far more ambitious. In an interview with TechFlash, Google Research Fellow Jeff Dean talked to Jon Xavier about his team’s work on machine learning and neural nets to expand Google’s abilities in conversational search …
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