Category Archives: In the News

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:

Untitled

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!

Stats Software Help @ WIC

yaniAt WIC, you can already get help with writing, speaking, technology, copyright and more. In addition, we’re glad to announce that Yani Liang will be providing assistance with statistical software including SPSS, STATA, R and Excel.

Yani can assist you with statistical software including SPSS, STATA, R and Excel.  She is willing to answer questions about proper commands in R, operations in SPSS, STATA, and EXCEL. She can also provide guide on statistic modeling and graphic design with explicit requirement. However, the assistance is not intended to help students choose the statistical methods, graph, or charts to be used for their research. How to conduct the data analysis and interpretation should be based on your own ideas and discipline-specific expectations.

Yani is a second year master student at School of Design, studying City Planning with a concentration in Transportation. Her statistical experience covers both natural science and social science. She has her Bachelor’s degree in Geography and Environmental Management, along with a Computer Science Minor from University of Waterloo.

Yani will be offering statistics help by appointment on Monday and Wednesday afternoons at WIC in room 116 starting on September 9th. You can request an appointment with her online.

Task your 3D mind to win these 3D challenges

As you might have noticed, the last couple of posts of mine have been about 3D printing and obviously this one is too. I just cannot stop my fascination with the subject. This morning, I found this page about 3D challenges. The news is too good to keep to myself, although sharing it could potentially put me at a disadvantage by decreasing the odds of getting my own MakerBot Replicator Desktop 3D Printer !

There you go! If you did not know it already, you can own a 3D printer – all you have to do is put your imagination to work and we can print out your creation at the Education Commons. Go Brains!

3D Printing Instructions Poster_FINAL(1)

2015 Video Contest Winners!

We congratulate the winners of the 2015 Video Contest: What Does Healthy Look Like?

  • First prize: Will Always Be Loved by Courtney Dabney
  • Second Prize:  Making Sense of Happiness by Meredith Stern
  • Third Prize: 8-Bit Distracted by Ivan Moutinho
  • Popular Choice Award: Outbreaks in Film by Lauren Drinkard

View the winners online.

We thank our judging panel of faculty, staff, students and alumni, and the many faculty who encouraged their students to participate in our annual contest!

Controlling Scholarship: Elsevier or Universities

Scholarship is the fuel on which modern universities rely. Without it, researchers cannot build upon the discoveries of their colleagues; students cannot learn from the expertise of others, and the progress of knowledge stagnates. Currently, that fuel is largely controlled by a small group of publishers, and with that control comes a great deal of power over how scholars distribute their work.

Recently, Elsevier ostensibly said they would like to help further the goal of sharing scholarship by “unleashing the power of academic sharing.” Yet, on closer review, Elsevier’s plan is really to do the exact opposite, and to increase their own revenues by inhibiting distribution. As a commercial company, it is hard to fault Elsevier for trying to make more money. Yet, there is a much larger issue at stake here.

On the surface, issues of network neutrality, rising costs in higher education, and growing income inequality seem unrelated to Elsevier’s policies on distributing academic articles. Yet, Prof. Lawrence Lessig, in a recent talk at the Association of College and Research Libraries suggested that many of these issues (including open access) are linked because they help to create a more equal society.

The question is: who is in the best position to create more equal access to scholarship? Is it companies like Elsevier? Or, is it the universities that rely on new research in order to continue functioning? According to 482 universities, including the University of Pennsylvania, the answer is resoundingly in favor of universities. Libraries, organizations, and individuals around the world are asking for a revision of this policy. More importantly, many of these organizations hope to find a better system for sharing scholarship.

So, what might seem to be an issue involving only institutional repositories, actually has much broader implications. Librarians may not be able to control debates on net neutrality, the spiraling costs of tuition or the growing inequality of income within society. We can, however, fight for equal access to research, and we can fight to ensure that universities, rather than for-profit corporations, control the fuel (i.e. scholarship) on which the academy relies.

For more information: