Tag Archives: Google

Gmail’s Smart Reply for you

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.

Example Autopilot Responses
©2011 Google

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.

io-highlights-googlee28099s-machine-learning-smartszImage 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.

reminders31
Image Source: http://www.gmailblog.blogspot.com

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?

Google AI
Image Source: http://www.lifehacker.com.au

 

 

 

How Big is Google?

It’s pretty big. A recent article in Wired  highlights how big Google actually is, at least in terms of code. All of Google’s services (Search, Mail, Maps, etc.) encompass 2 billion lines of code stored in one place and shared by 25,000 developers. The graph below illustrates just how big 2 billion lines of code is:

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Microsoft Windows, “one of the most complex software tools ever built for a single computer, a project under development since the 1980s” is significantly smaller than the massiveness of Google.

Although Google’s repository is not open source, it is shared between roughly 25,000 developers who can add and modify code collaboratively. For now Google is an extreme case, but in the future more companies may need to handle gargantuan amounts of code. Facebook and Google are working together on an open source version control system to allow other companies to safely and cleanly house, modify, and create code on a large scale.

Interested in more? Check out the Million Lines of Code graphic for more examples or read the Reddit thread on the topic.

Check out some of our other posts about Google. Interested in learning new tech tools? You can request a training session or check out our monthly WICshop calendar for upcoming events!

Doing effective research with databases

Yuting Wang has been a graduate student intern with us at the Weigle Information Commons for the past year. In the post below, she reflects on her research experiences at Penn as she completes her Masters of Education in Teaching English to Speakers of Other Languages (TESOL):

Having submitted my 50-page thesis paper for my master’s degree, I eagerly await commencement.  I feel so excited and relieved at this moment.  However, looking back on all the assignments I have done in the past two years as a graduate student, I wonder how much time I have spent on doing research on literature reviews before starting to write my papers.  I guess every student in college or graduate school has experienced the process of searching for suitable articles/sources for assignments. I would like to thank all the librarians who have helped me to go through this process . It is their help that makes my research more effective.

Continue reading Doing effective research with databases

Join us for Gadget Day on Friday, April 26

gadgetday_toprightbox611x298(1) Register now for our spring Gadget Day! We collected gadget ideas from around campus this spring. It will be a fast-paced day with lots of devices to explore.

Caitlin Shanley will start the day with SlideShark, an app that controls your PowerPoint from your iPhone. Charles Washington from Penn GSE will show the Swivl, a clever way to video-record a pacing presenter. Oliver Jenkins, who  recently wrote about CamScanner, will share his favorite apps, and Chris Martin will discuss Kelly Writers House experiences with Google Hangouts on Air. Continue reading Join us for Gadget Day on Friday, April 26

2013 Tech Resolutions

Happy new year!

We’re sure you have a few resolutions of your own in this month of good intentions (my favorite one I’ve heard so far is “stop reading the comments“), but David Toccafondi and I thought we’d share a few suggestions for tech-related resolutions to help start off 2013 right. See our list below, and let us know about yours in the comments! Continue reading 2013 Tech Resolutions

Google Search by Image

Inspired by WIC librarian Caitlin Shanley’s post about Google Power Searchers, I thought I’d share some pointers on image searching that I’ve learned recently. While working on image copyright for Penn’s offerings on Coursera.org—a platform for free online classes from top universities— I’ve become well-acquainted with Google’s Search by Image feature. I was surprised to find out that not too many people know about this useful tool! It’s a great solution for common frustrations like:

  • I saved an image to my desktop to put in a paper, but now I can’t remember the source to cite it.
  • I have a picture of a plant/creature/landmark/item/work of art, and I want to get information about it.
  • I want to reuse an image on the web, but I need to track down the owner to get permission.
  • I want to find the original source of a pinned image on Pinterest.
  • I want to find a better resolution or uncropped version of an image.
  • I’m an artist/creator monitoring reuse of my work.
  • I want to find pictures of cats that look like my cat.

Here’s how it works: You can search with an image whether it’s online or saved to your hard drive– just head over to Google Images and click the little camera icon on the far right side of the search bar. Continue reading Google Search by Image