"<i>applies these same high-powered analytics to relate [...] events broadcast on TV to conversations taking place in social media</i>"<p>So, if you use Twitter, you're someone's lab rat. I know that when I tweet, it's open for all the world to see, but I can't shake the feeling that this is really creepy.<p>Beyond that, I'm trying to envision how this data could be used. I imagine three scenarios:<p>1. Leverage it to sell more TV advertising. If a show is getting buzz on twitter, maybe this could be a viable alternative to Nielsen ratings. (Which leads to the question of whether Blue Fin can discern positive buzz from negative buzz).<p>2. If step 1 is analysis, could step 2 be manipulation? Can buzz be jump started or boosted at key inflection points by sock puppet marketing?<p>3. C-level eye candy - interesting visualizations that TV exec's buy for their egos, but ultimately can't do anything actionable with the information.
So the language acquisition stuff could be an n=1 just-so story, but meanwhile:<p>Deb Roy and Phil Decamp just invented a way to efficiently browse <i>days</i> of multiple video streams - on <i>paper</i>, if you want:<p><a href="http://video.fastcompany.com/plugins/player.swf?v=2014e22b27618&p=fc_social" rel="nofollow">http://video.fastcompany.com/plugins/player.swf?v=2014e22b27...</a><p>Their work on "time worms" is astounding; unfortunately, the video ends before zooming out to the next step: multitrack timeworms with hundreds of cameras; broadband recordings of ALL THE CHANNELS.<p><a href="http://www.youtube.com/watch?v=RE4ce4mexrU&t=11m56s" rel="nofollow">http://www.youtube.com/watch?v=RE4ce4mexrU&t=11m56s</a><p>We can put off the hard problem of CV-driven video search; we can solve the much easier problem of "leverage people's brains to recognize patterns". Visualizations are the new algorithm.
I think a better summary would by "MIT professor collects 90,000 hours of video of his son's first words, gets tenure based on that, does nothing with the data. With tenure safe in hand, leaves his students in a lurch as he heads off to do a start-up."<p>It's a great corpus he collected. Wish he either had a longer attention span, or at least bothered to share the data.
I keep a git repository[1] of my son's (1,5 years old) keyboard hammering. He "types" until he accidentally leaves insert mode in Vim or leaves the computer, and then I commit it.<p>In 5-10 years time I hope to be able to do some real-time visualization with milestones like "first real word", "first use of <i>complicated word</i>", etc. If he's interested I might track his first code there as well.<p>1: <a href="https://github.com/jacobrask/Ivar" rel="nofollow">https://github.com/jacobrask/Ivar</a>
The MIT project sounds awesome and I love the visualization. I was underwhelmed by the offshoot company called Bluefin Labs. For such awesome research at MIT, it seems like Bluefin is basically Twitter trending for TV shows.
I was disappointed.<p>The graphics/visualization is breathtaking but what they learned from all of that analysis seems very limited: Apparently, when caregivers discover that a child is learning a word they simplify their use of that word till the child grasps it and then revert back to normal usage once the child can use the word.<p>It could very well be that their regular usage of the word that the child is learning is unaffected, but in addition they use the word more often in simple sentences around the child, and once the child understand the word revert back to regular usage patterns/frequency. That would explain the results and does not seem that interesting.
Not related to his project, but I feel very proud in a distant way. My last startup's office (in Kolkata, India) was at his father's house.
Don't know why I wrote that, just felt...
I liked the example with the president's speech. It won't be long before politicians will adjust their speeches during the speech according to the reactions from viewers.