The TSA is statistically about 50% correct, China to send a rover to the moon, breaking the filter bubble, and how BitCoin really works.
Ben and Lyle loved this episode!
The most damning info comes from a broad analysis of the program in 2011 and 2012, which found wildly different techniques and rates of success. The report also highlights the extensive scientific literature on the human ability to identify deceptive behavior. Summarizing 400 studies over the past 60 years, the report concludes that humans perform only “the same as or slightly better than chance.” Given that the TSA has spent almost a billion dollars on the program, that’s a pretty poor record. As a result, the GAO is requesting that both Congress and the president withhold funding from the program until the TSA can demonstrate its effectiveness.
Bigelow is applying to the Federal Aviation Administration’s Office of Commercial Space Transportation to amend a 1967 international agreement on the moon so that a system of private property rights can be established there. “When there isn’t law and order,” he said, “there’s chaos.”
A Chinese Long March rocket is scheduled to blast off to the Moon on Sunday evening at about 6pm UTC carrying a small robotic rover that will touch down on to the lunar surface in about two weeks’ time – the first soft landing on the Earth’s only natural satellite since 1976.
An interesting story on research about breaking the socially based “filter bubble.”
“Bitcoin is an open source peer-to-peer electronic money and payment network introduced in 2009 by pseudonymous developer ‘Satoshi Nakamoto’.”
“…Until recently, the executives of most companies served by data centers did not put much thought into energy either. High electricity bills were taken as a sign of thriving business. And by that measure, business is great. Facebook users upload 350 million photos, send more than 10 billion messages, and click nearly 5 billion likes every day. All that activity requires enough electricity to power a city of 155,000 people. Google could power a metropolis of 750,000, larger than Boston, Seattle, or Denver. Globally, power consumption at data centers rose by 63 percent last year, to 38 gigawatt-hours—an amount equivalent to the annual electricity usage of New Zealand or Colombia.”
Just listened to your show on filter bubbles, good one. Just one point, the guy who coined the term is highly biased and some of his example are not very good (he runs a competing search engine not good enough to do personalized searches).
For example, he picked “BP” at the time of the spill and complained that it only showed stocks to some people and information about bio hazard to others. But as googler Matt Cutts pointed at the time (can’t find the link), searching for “BP” only is not enough information for Google, it has to guess a lot of stuff and will try to use personalized stuff, if you actually want to search about the BP stock value, you should just search for “BP stock” and if you’re looking for the hazards you should be looking for “BP geo hazards”, that’s what people do. Who does random searches about BP only? Google is smart but not to the point of guessing so much information. Another point by Matt Cutts
We do have algorithms in place designed specifically to promote variety in the results page. For example, you can imagine limiting the number of results returned from one single site to allow other results to show up instead. That helps with the diversity of the search results. When trying to find the best search results, we look at relevance, diversity, personalization, localization, as well as serendipity and try to find the best balance we can.
Also a good point of his on why personalized search is relevant:
But aren’t you a part of the relevance equation? The ideal results for a search like [bitcoin crash] should be different for a Japanese-speaking searcher in Tokyo vs. a German-speaking searcher in Munich vs. a bitcoin expert vs. a programmer trying to diagnose why compiling bitcoin is crashing vs. my Mom who has never heard of bitcoin before, right?