Rather, the online component of the product is a service that connects customers, their storage devices, and the users they invite together so they can share information. Were Pogoplug to go belly-up tomorrow, nobody would lose data, only the access to the transfer service they paid to use. If the worst happens and Pogoplug does shut down, whoever restarts the service would have to re-gain the trust of users, who would need to re-configure their accounts and get new passwords to use the service again.
Even so, I like the dead-man's switch aspect to Pogoplug's escrow plan. While it won't guarantee that the product will resurrect if the company dies, it does at least make it possible--maybe even likely. I'm surprised more companies, especially Web companies that store customer data, don't have public doomsday plans.
If you buy life insurance, it's not an admission of weakness. It does not telegraph that you expect to die tomorrow. But if you've got a family of customers to support, the insurance can be a smart thing to have. Be respectful, keep it civil and stay on topic. We delete comments that violate our policy , which we encourage you to read. Discussion threads can be closed at any time at our discretion.
In fact, this is a file server your parents could run themselves. Harry Teasley has been developing video games professionally for nearly 20 years, working on such blockbuster games as Half-Life and Halo. Lossless data compression seems a bit like a magic trick. Its cousin, lossy compression, is easier to comprehend.
Lossy algorithms are used to get music into the popular MP3 format and turn a digital image into a standard JPEG file. They do this by selectively removing bits, taking what scientists know about the way we see and hear to determine which bits we'd least miss.
But no one can make the case that the resulting file is a perfect replica of the original. Not so with lossless data compression. Bits do disappear, making the data file dramatically smaller and thus easier to store and transmit. The important difference is that the bits reappear on command. It's as if the bits are rabbits in a magician's act, disappearing and then reappearing from inside a hat at the wave of a wand. The world of magic had Houdini, who pioneered tricks that are still performed today.
And data compression has Jacob Ziv. LZ77 wasn't the first lossless compression algorithm, but it was the first that could work its magic in a single step. Photo: Rami Shlush. D, MIT, National Academy of Engineering, U. The following year, the two researchers issued a refinement, LZ Without these algorithms, we'd likely be mailing large data files on discs instead of sending them across the Internet with a click, buying our music on CDs instead of streaming it, and looking at Facebook feeds that don't have bouncing animated images.
Ziv went on to partner with other researchers on other innovations in compression. Ziv was born in to Russian immigrants in Tiberias, a city then in British-ruled Palestine and now part of Israel.
Electricity and gadgets—and little else—fascinated him as a child. While practicing violin, for example, he came up with a scheme to turn his music stand into a lamp.
He also tried to build a Marconi transmitter from metal player-piano parts. When he plugged the contraption in, the entire house went dark. He never did get that transmitter to work. When the Arab-Israeli War began in , Ziv was in high school. Drafted into the Israel Defense Forces, he served briefly on the front lines until a group of mothers held organized protests, demanding that the youngest soldiers be sent elsewhere.
Ziv's reassignment took him to the Israeli Air Force, where he trained as a radar technician. When the war ended, he entered Technion—Israel Institute of Technology to study electrical engineering. After completing his master's degree in , Ziv returned to the defense world, this time joining Israel's National Defense Research Laboratory now Rafael Advanced Defense Systems to develop electronic components for use in missiles and other military systems.
The trouble was, Ziv recalls, that none of the engineers in the group, including himself, had more than a basic understanding of electronics.
Their electrical engineering education had focused more on power systems. It wasn't enough. The group's goal was to build a telemetry system using transistors instead of vacuum tubes. They needed not only knowledge, but parts. Ziv contacted Bell Telephone Laboratories and requested a free sample of its transistor; the company sent In , Ziv was selected as one of a handful of researchers from Israel's defense lab to study abroad.
That program, he says, transformed the evolution of science in Israel. Its organizers didn't steer the selected young engineers and scientists into particular fields. Instead, they let them pursue any type of graduate studies in any Western nation.
Ziv planned to continue working in communications, but he was no longer interested in just the hardware. He had recently read Information Theory Prentice-Hall, , one of the earliest books on the subject , by Stanford Goldman, and he decided to make information theory his focus. And where else would one study information theory but MIT, where Claude Shannon, the field's pioneer, had started out?
Ziv arrived in Cambridge, Mass. His Ph. So if you invest the computational effort, you can know you are approaching the best outcome possible. Ziv contrasts that certainty with the uncertainty of a deep-learning algorithm. It may be clear that the algorithm is working, but nobody really knows whether it is the best result possible.
He found this work less beautiful. That is why I didn't go into real computer science. There are many options available, depending on the size of the customer and as such the process would be customer-dependent. Why do these options whatever they are have to wait until contract negotiations?
I can understand that the price might be, but keeping the options secret does not help those who are try to decide if the Imp is the right answer or not. In another post you said that communicating has taken a back seat to developing features. I would like to suggest they are co-equal in importance.
As a developer, yes I need new features, but I also need to have some kind of idea as to when they might be delivered, and what they are.
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