NYU Data Science newsletter – June 2, 2016

GROUP CURATION: N/A

Automated personal assistants such as Google Now, Microsoft Cortana, Siri, M and Echo aid users in productivity-related tasks, e.g., planning, scheduling and reminding tasks or activities. In this paper we study one such feature of Microsoft Cortana: user-created reminders. Reminders are particularly interesting as they represent the tasks that people are likely to forget. Analyzing and better understanding the nature of these tasks could prove useful in inferring the user’s availability, aid in developing systems to automatically terminate ongoing tasks, allocate time for task completion, or pro-actively suggest (follow-up) tasks.

Disease surveillance systems largely focus on infectious diseases with high mortality, whereas less severe diseases often go unreported. Using chicken pox as an example, we demonstrate that Internet queries can be used as a proxy for disease incidence when reporting is lacking. We established that Google Trends accurately reflected clinical cases in countries with surveillance, and thus population-level dynamics of chicken pox. Then, we discovered robust seasonal variation in query behavior, with a striking latitudinal gradient on a global scale. Next, we showed that real-time data-mining of queries could forecast the timing and magnitude of outbreaks. Finally, our analyses revealed that countries with government-mandated vaccination programs have significantly reduced seasonality of queries, indicating vaccination efforts mitigated chicken pox outbreaks.

To investigate the nature of past AI predictions and cycles of optimism and pessimism in the history of the field, I read or skim-read several histories of AI and tracked down the original sources for many published AI predictions so I could read them in context. I also considered how I might have responded to hype or pessimism/criticism about AI at various times in its history, if I had been around at the time and had been trying to make my own predictions about the future of AI.

Farmobile is proud to offer the world’s first data store to fairly compensate farmers for their digital assets.
We are launching our pilot program in Minnesota and plan to expand to other geographies soon.

Text is a prevalent form of communication on Facebook. Understanding the various ways text is used on Facebook can help us improve people’s experiences with our products, whether we’re surfacing more of the content that people want to see or filtering out undesirable content like spam.

With this goal in mind, we built DeepText, a deep learning-based text understanding engine that can understand with near-human accuracy the textual content of several thousands posts per second, spanning more than 20 languages.

Exclusive social groups are ones in which the group members decide whether or not to admit a candidate to the group. Examples of exclusive social groups include academic departments and fraternal organizations. In the present paper we introduce an analytic framework for studying the dynamics of exclusive social groups.

Today’s post is all about ICLR 2016. I’ll highlight new strategies for building deeper and more powerful neural networks, ideas for compressing big networks into smaller ones, as well as techniques for building “deep learning calculators.” A host of new artificial intelligence problems is being hit hard with the newest wave of deep learning techniques, and from a computer vision point of view, there’s no doubt that deep convolutional neural networks are today’s “master algorithm” for dealing with perceptual data.

Ad tech ate the world, but Facebook is eating ad tech, at least from the perspective of the industry that was born before the social network began dominating internet advertising.

Last week alone, Facebook shut down its last pure programmatic ad exchange FBX, put the final nail in the LiveRail platform, and expanded its Facebook Audience Network, which is a closed platform. These changes, dripped out over months, have put a scare in the ad tech ecosystem of intermediaries that often bid on ad impressions in open exchanges.

Also, at Facebook:

Introducing DeepText: Facebook’s text understanding engine (June 01, Facebook Code, Engineering Blog)

As a conservative Republican from the West and a liberal Democrat from the Midwest, senators Cory Gardner (R–CO) and Gary Peters (D–MI) are separated by geography and ideology. But they see eye-to-eye on the need for the federal government to strengthen its support of basic research.

In the next few weeks, the U.S. Senate is expected to begin rewriting a bill governing federal policies toward research, innovation, and science education. And if the stance that Gardner and Peters have taken is any guide, the legislation could help restore a bipartisan consensus on the topic that has been sorely lacking in Congress in recent years.

The ‘reproducibility crisis’ in science appears to be a widespread problem that may have its roots in the ‘publish or perish’ culture of the contemporary academy. Facilitated by a well-developed culture of data sharing, in astrophysics opportunities to reproduce or replicate published results have been part of the field’s fabric for many decades. The valuable lessons learned from this small discipline could easily be rolled out to other data-rich disciplines. This essay aims at triggering more extensive discussion of the numerous advantages of data sharing and responsible research attitudes.

… MOTHERBOARD: Hey Harper. Have the presidential candidates of 2016 been looking at the things you did in 2012?

HARPER REED: I am mostly afraid that we will accidentally elect a Nazi as president.

You’ll see that every campaign has embraced the importance of data. However, I’d like to debunk the idea that data is the most important aspect.

We are searching for the next Data Science Bowl challenge—a problem with the potential to change the world. We need you to share your ideas. If selected, the power of the entire data science community will be harnessed against it. Submit your ideas to DataScienceBowl@bah.com.

Deadline for submissions is in advance of the competitions which is scheduled to begin on Monday, December 12.

It’s been awhile since we launched a whole new product at Fog Creek Software (the last one was Trello, and that’s doing pretty well). Today we’re announcing the public beta of HyperDev, a developer playground for building full-stack web-apps fast.

HyperDev is going to be the fastest way to bang out code and get it running on the internet. We want to eliminate 100% of the complicated administrative details around getting code up and running on a website. The best way to explain that is with a little tour.