New data analysis competitions



  • Google, not GCHQ, is the truly chilling spy network.

    Given how central the network has become to our lives, that means our societies have embarked on the greatest uncontrolled experiment in history. Without really thinking about it, we have subjected ourselves to relentless, intrusive, comprehensive surveillance of all our activities and much of our most intimate actions and thoughts. And we have no idea what the long-term implications of this will be for our societies - or for us as citizens.

    One thing we do know, though: we behave differently when we know we are being watched. There is lots of evidence about this from experimental psychology and other fields, but most of that comes from small-scale studies conducted under controlled conditions.

  • European Parliament Committee Recommends End-To-End Encryption For All Electronic Communications.

    The European Parliament's (EP’s) Committee on Civil Liberties, Justice, and Home Affairs released a draft proposal for a new Regulation on Privacy and Electronic Communications. The draft recommends a regulation that will enforce end-to-end encryption on all communications to protect European Union citizens' fundamental privacy rights. The committee also recommended a ban on backdoors.

  • DHS Is Starting to Scan Americans' Faces Before They Get on International Flights.

    Decades ago, Congress mandated that federal authorities keep track of foreign nationals as they enter and leave the United States. If the government could record when every visitor stepped on and off of U.S. soil, so the thinking went, it could easily see whether a foreign national had overstayed a visa.

    But in June of last year, without congressional authorization, and without consulting the public, the Department of Homeland Security started scanning the faces of Americans leaving the country, too.


  • An Artificial Intelligence Developed Its Own Non-Human Language.

    A buried line in a new Facebook report about chatbots' conversations with one another offers a remarkable glimpse at the future of language.

    In the report, researchers at the Facebook Artificial Intelligence Research lab describe using machine learning to train their "dialog agents" to negotiate. (And it turns out bots are actually quite good at dealmaking.) At one point, the researchers write, they had to tweak one of their models because otherwise the bot-to-bot conversation "led to divergence from human language as the agents developed their own language for negotiating." They had to use what's called a fixed supervised model instead.

  • Data-Mining 100 Million Instagram Photos Reveals Global Clothing Patterns.

    The question these guys specifically want to answer was how clothing styles vary around the world, a cultural phenomenon that is otherwise difficult to study on this scale.

    For example, their approach can tackle questions such as how the frequency of scarf use in the U.S. is changing over time, what styles are most specific to particular regions or cities, and, conversely, which styles are popular across the world.

  • Facebook teaches bots how to negotiate. They learn to lie instead.

    The Facebook Artificial Intelligence Research (FAIR) group, in collaboration with Georgia Institute of Technology, has released code that it says will allow bots to negotiate. The problem? A paper published this week on the R&D reveals that the negotiating bots learned to lie. Facebook’s chatbots are in danger of becoming a little too much like real-world sales agents.

  • Help EFF Track the Progress of AI and Machine Learning. The work notebook is amazing.

    This pilot project collects problems and metrics/datasets from the AI research literature, and tracks progress on them.

  • Google Unveils an AI Investment Fund. It's Betting on an App Store for Algorithms. The cyberpunk future in which you could rent algorithms is here (it's been here for a while now, but this is closer to what sci-fi envisioned).

    The company disclosed today that it has created a new venture fund dedicated to investing in AI and machine learning companies. The initiative's first public investment: lead investor in a $10.5 million funding round for Seattle startup Algorithmia, which has built a kind of app store for algorithms. The service aims to make it easier for any company to use machine learning.

Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.

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