Not really if you define (as Amazon would) efficiency as order throughput and cost-per-order. Humans are typically more expensive than robots per hour: robots cost upfront and then maintenance + energy, but if those sum up to an hourly rate beyond the cost of humans for a jobs that humans can do at comparable quality... you wouldn't have robots yet. Kiva exists and continues to get deployed...
To fulfill an order with Kiva, a human stands at a ship station (boxes, label printing, tape) near a fast path (door, belt) to outbound. Shelves are brought, the human picks the item from the shelves and assembles the order. That's putting the humans in the loop where robotics is harder/more expensive. Your hard fulfillment rate limit is then the time it takes the human to pick and assemble the order, plus whatever time it takes the robots to bring the shelves over. This scales gracefully (install more robots until the hard latency of order fulfillment becomes robot travel time from the farthest shelf to the human, plus human time) -- robots scale with the number of shelves, humans scale with the number of fulfillment stations.
To fulfill via Segway, you tie up a human for the entire travel time between station and the traveling salesman problem of order picking and back. Or you do as Amazon was doing in this article, and split pick and pack and allow for subdividing orders between pickers, and so on. This works (obviously) and the segway approach would likely improve fulfillment speed for pickers. But it does not save operating expense (headcount).
Recs (therecordstream.com) is great for this. A JSON log file would be interpreted as its native record format, so you can use all of its processing tools (like recs-grep and recs-collate and recs-sort).
This is nice, simple experiment design. However, I'm really surprised they only ran this once - or indicate trial counts and indicate range/distribution. I'd be curious if video transcoding is so consistent that a single measurement is enough to draw a conclusion; certainly network/storage transfer is not. Sure, time and bandwidth are not free...
If this is appealing, I recommend trying RecordStreams (http://code.google.com/p/recordstream/). I use it for ad hoc Big Data command line analysis almost daily.
Consider the MOTOFONE. Fancy e-Ink display, but has battery life measured in days. Designed for the third world market, it can text message... badly, and that's it beyond good call quality.
NitroPDF does a remarkably good job translating PDF to Doc and RTF. I think the application (windows :() is better/has more output options, but they have a free web service: http://www.pdftoword.com/
Are you doing this on the site listed in your profile? From what I can see with a 27ms RTT request, there is a 9ms pause after the GET ACK and content -- and then only 4 full packets before an RTT. That's close to the limit of my initial window (5880) before content ACKs arrive. That would seem like a typical result unless/until clients start tuning their initial window as well... which was kind of the point of Google going public on this. Have you seen much aggregate benefit beyond a window increase from 2 to 4?
Having the body control to produce false, seemingly involuntary signals - while suppressing true involuntary signals - implies a level of physical mastery to the extent that you, likely, already possess a substantial advantage in the bout. This is like selling a fake tell in poker while not actually having a tell - even James Bond would tell you that's hard.
And the latter two provide immediately accessible numbers. Alpha Project "is a nonprofit human services organization that serves over 2,000 men, women, and children each day." The Regional Taskforce for Homelessness in San Diego published a 2009 overview (PDF, http://www.rtfhsd.org/pdf/PITC09.pdf) indicating at least 7892 counted within the San Diego area, at least 4338 in San Diego City.
Those are facts, and they took one minute to acquire. If your point was that there were less per capita, I cannot argue with that as I do not have comps.
Actually, it is not trivial to programmatically extract plain text from a PDF in a consistent format. In many cases it is easy, but the PDF format is visual first and content second, resulting in plenty of opportunities for Captcha-like problems.
Despite that, PDF, especially PDF-A, is the superior format for preserving published content.
Not a folk tale, just a visible representation of the local competitive environment. Animals in the Galapagos are generally less flighty because the entire ecosystem is not very competitive: everyone lives off the bounty of the sea. The booby birds, the iguanas, the tortoises... are not intimidated by us because there are no land or air predators to eat them -- not in their risk profiles. Like any other security measure, you optimize for the challenges you expect.
In other environments, apex predators still have a flight response because they still have predatory competition (e.g., wolves against other wolves, or other dangerous situations). The flight response increases based on individual vulnerability - e.g., a well-fed pride of lions will barely observe nearby vehicles on safari (they are some of the most self-confident animals you may encounter) but hungrier singles take more notice.
No, they are probably not looking for that answer - but failure to accept them (with working code) would be a negative corporate indicator. An interviewer shouldn't look for answers like that because it requires some amount of fibonacci domain knowledge, which, unless the company specifically works with fibonacci (or similar math), would be a pretty odd filter criteria for programmer quality.
To fulfill an order with Kiva, a human stands at a ship station (boxes, label printing, tape) near a fast path (door, belt) to outbound. Shelves are brought, the human picks the item from the shelves and assembles the order. That's putting the humans in the loop where robotics is harder/more expensive. Your hard fulfillment rate limit is then the time it takes the human to pick and assemble the order, plus whatever time it takes the robots to bring the shelves over. This scales gracefully (install more robots until the hard latency of order fulfillment becomes robot travel time from the farthest shelf to the human, plus human time) -- robots scale with the number of shelves, humans scale with the number of fulfillment stations.
To fulfill via Segway, you tie up a human for the entire travel time between station and the traveling salesman problem of order picking and back. Or you do as Amazon was doing in this article, and split pick and pack and allow for subdividing orders between pickers, and so on. This works (obviously) and the segway approach would likely improve fulfillment speed for pickers. But it does not save operating expense (headcount).