Hilary Mason

Author: hmason

  • Et tu, Google?

    Posted: April 14, 2013 | Author: | Filed under: blog | Tags: , | 4 Comments »

    In 2008, cuil, a search engine startup, displayed my bio alongside a photo of deceased actress Hilary Mason. In January 2013, Bing confused us, this time putting my photo next to her bio (they fixed it after a suitable amount of mocking on Twitter).

    Today, Google did the same thing. (live search link)

    Today I win the internet?

    Screen Shot 2013-04-14 at 4.59.24 PM

    If you zoom in on the bio section, you can clearly see that it’s her bio with a photo of me (originally from Crain’s New York 40 under Forty). Further, if you go into her filmography, you continue to see my photo.

    I’m most proud of my starring role in the amazing film Robot Jox. (bottom right of the image below)

    robot_jox

    I know that entity disambiguation is a hard problem. I’ve worked on it, though never with the kind of resources that I imagine Google can bring to it. And yet, this is absurd!

    Note: It’s also been pointed out to me that there’s a slim possibility that Google’s confusion stems from my own post about Bing’s error, in which case, this post will certainly make the confusion worse. To that I say — bring it on, technofuture irony!

     

  • Data Engineering

    Posted: April 1, 2013 | Author: | Filed under: blog | Tags: , , , | 3 Comments »

    Data engineering is when the architecture of your system is dependent on characteristics of the data flowing through that system.

    It requires a different kind of engineering process than typical systems engineering, because you have to do some work upfront to understand the nature of the data before you can effectively begin to design the infrastructure. Most data engineering systems also transform the data as they process it.

    Developing these types of systems requires an initial research phase, where you do the necessary work to understand the characteristics of the data, before you design the system (and perhaps even requiring an active experimental process where you try multiple infrastructure options in the wild before making a final decision). I’ve seen numerous people run straight into walls when they ignore this research requirement.

    Forget Table is one example of a data engineering project from our work at bitly. It’s a database for storing non-stationary categorical distributions. We often see streams of data and want to understand what the distributions in that data look like, knowing that they drift over time. Forget Table is  designed precisely for this use, allowing you to configure the rate of change in your particular dataset (check it out on github).

  • Why Google Now is Awesome

    Posted: March 23, 2013 | Author: | Filed under: blog | Tags: | 8 Comments »

    google-now-cardsGoogle Now is an extension to Google’s Android search app that uses all of the data that Google has about you along with what it can guess about your current context to present the information it thinks you need when it thinks you need it.

    It’ll tell you to leave a bit early to make your next calendar event because of heavy traffic, or that it’s a friend’s birthday, or that there’s a cool cafe nearby where you are.

    I think it’s amazing.

    It’s amazing because this is the first Google product that takes ALL OF THE DATA that they have about us and actually makes it useful for us. Not for advertisers.

    Finally.

  • A (short) List of Data Science Blogs

    Posted: February 25, 2013 | Author: | Filed under: blog | Tags: , | 4 Comments »

    I’m gathering a bundle of data science blogs to share. I’m looking to include blogs that update regularly and aren’t either personal opinion and project blogs (like this one) or primarily about marketing any particular company. Let me know if you have a favorite that I’ve forgotten.

    If you’re just looking for one place to start, hop on over to Simply Statistics.

  • Experimenting With Physical Graphs

    Posted: February 4, 2013 | Author: | Filed under: blog | 4 Comments »

    I ended up at NYC Resistor on Sunday, and decided to experiment with physical visualization of some data. I grabbed the clicks per second on keyphrases including my name (“hilary mason”) over the last six months, aggregated them by day, and made this graph:

    attention on hilary mason

    This is easy enough to construct for any phrase using the clickrate data that we’re calculating at bitly. I exported it from matplotlib in svg, added a label, and used the laser-cutter to create this out of plywood:

    laser-cut time series

    laser-cut time series

    …which will shortly be adorning my desk at work. This is very simple, but there’s a lot of fun to be had with the physical manifestation of patterns we see in large amount of ephemeral data.