Back in 2009, Google teased users with Gmail Autopilot, a service which would both read and respond to emails automatically. The service would get to know you by reading your emails and being responding using your personal communication style. Of course, people quickly recognized this as an infamous Google hoax.
This may have seemed far-fetched six years ago, but personal, automated email responses are now becoming a reality thanks to Google’s new artificial intelligence technology:
“Google just unveiled technology that’s at least moving in that direction. Using what’s called “deep learning”—a form of artificial intelligence that’s rapidly reinventing a wide range of online services—the company is beefing up its Inbox by Gmail app so that it can analyze the contents of an email and then suggest a few (very brief) responses. The idea is that you can rapidly respond to someone while on the go—without having to manually tap a fresh message into your smartphone keyboard.”
Google’s “deep learning” technology, called ‘Smart Reply,’ now allows Gmail to analyze the content of your email and suggest a few brief responses to it. In this process, composing new mail can be substituted by this new bit of Google’s artificial intelligence.
According to Google’s product Manager Alex Gawley, Smart Reply will tailor both tone and content of the email and suggest three responses. The user can still choose to either use one of them or modify them with one’s own words.
Image Source: http://www.techroc.com
This particular feature of Gmail is a result of something called ‘Machine Learning.’ Pieces of information from all over the world are constantly fed into a neural network (a network of computers intended to represent and perform functions of neurons in the human brain) called long short-term memory (LSTM system). One half of this neural network on receiving these new pieces of information analyzes them and ‘learns’ the underlying patterns in diverse sets of phrases in the language. The second half works on generating potential responses (typically 3-6 words long), one word at a time.
For example, by feeding enough pictures of a human, the machine eventually ‘learns’ how to identify a human. However, this feature is not new. It can be thought of as an extension of the ‘suggest search’ feature in the Google Search engine, the ‘auto-complete’ feature on our phones’ texting applications, or the personal assistants, Siri or Cortana, on our phones.
Naturally, this feature depends on the amount of data input into a neural network. With only a finite amount of data, the machine’s responses can be rudimentary at best. Nevertheless, this technology is a leap in that direction.
Rumors are that this machine can even process jokes and suggest appropriate responses to them!
Welcome to the future! Comment here and let us know what you think. Fascinating use of technology or unnecessary AI intervention?