Interesting. I note that Amazon was down but Google stayed up through this leap second. This comes just as Google announced that they are now going to be offering web services:
http://gigaom.com/cloud/why-google-comp ... ces-users/
Interesting. I note that Amazon was down but Google stayed up through this leap second. This comes just as Google announced that they are now going to be offering web services:
Limited Run alleges 80 percent of clicks were coming from bots, and Facebook would only let the company change its name if it agreed to spend $2,000 or more in advertising a month.
Ah, yes. "Do not fold, staple, spindle or mutilate."Typhoon wrote:For those of you old enough to remember . . .
LcwxW2ne-UU
Pretty cool. My father's thesis project (simulations of car crashes) is in some boxes of IBM punch cards. I see the analysis program is written in Python. Is Python worth knowing? I already know Basic, Visual Basic, VBA, Fortran and C (also some statistical and mathematical packages). I hear codecademy has Python courses now.Antipatros wrote:Ah, yes. "Do not fold, staple, spindle or mutilate."Typhoon wrote:For those of you old enough to remember . . .
LcwxW2ne-UU
And then later, when the Hollerith analysers were no longer physically present, they continued to control us from the grave by making us insert "spunch=-punch", etc., in every flaming print command.
For all their progress, computers are still pretty unimpressive. Sure, they can pilot aircraft and simulate nuclear reactors. But even our best machines struggle with tasks that we humans find easy, like controlling limbs and parsing the meaning of this paragraph.
It’s a little sobering, actually. The average human brain packs a hundred billion or so neurons — connected by a quadrillion (10E15) constantly changing synapses — into a space the size of a cantaloupe. It consumes a paltry 20 watts, much less than a typical incandescent lightbulb. But simulating this mess of wetware with traditional digital circuits would require a supercomputer that’s a good 1000 times as powerful as the best ones we have available today. And we’d need the output of an entire nuclear power plant to run it
Closing this computational gap is important for a couple of reasons. First, it can help us understand how the brain works and how it breaks down. There is only so much to learn on the coarse level, from imagers that show how the brain lights up when we remember a joke or tell a lie, and on the fine level, from laboratory studies of the basic biology of neurons and their wirelike dendrites and axons. All the real action happens at the intermediate level, where millions of networked neurons work in concert to produce behaviors you couldn’t possibly predict by watching a handful of neurons fire. To make progress in this area you need computational muscle.
And second, it’s quite likely that finding ways to mimic the brain could pave the way to a host of ultraspeedy, energy-efficient chips. By solving this grandest of all computational challenges, we may well learn how to handle many other difficult tasks, such as pattern recognition and robot autonomy.
Fortunately, we don’t have to rely on traditional, power-hungry computers to get us there. Scattered around the world are at least half a dozen projects dedicated to building brain models using specialized analog circuits. Unlike the digital circuits in traditional computers, which could take weeks or even months to model a single second of brain operation, these analog circuits can model brain activity as fast as or even faster than it really occurs, and they consume a fraction of the power. But analog chips do have one serious drawback—they aren’t very programmable. The equations used to model the brain in an analog circuit are physically hardwired in a way that affects every detail of the design, right down to the placement of every analog adder and multiplier. This makes it hard to overhaul the model, something we’d have to do again and again because we still don’t know what level of biological detail we’ll need in order to mimic the way brains behave.
To help things along, my colleagues and I are building something a bit different: the first low-power, large-scale digital model of the brain. Dubbed SpiNNaker, for Spiking Neural Network Architecture, our machine looks a lot like a conventional parallel computer, but it boasts some significant changes to the way chips communicate. We expect it will let us model brain activity with speeds matching those of biological systems but with all the flexibility of a supercomputer....
On my last trip, in July, I met a ‘procurement’ consultant, and he told me which of the 50 mega malls in the area to visit to buy tablets.
In the US, when we talk about tablets we usually mean the iPad and increasingly the Kindle devices, but beyond that there is not much else in the market. I had heard that tablets in China had already reached low price points. You can buy a reasonable Android phone for $100 retail, and I wanted to see if I could find a $150 tablet. This consultant pointed me to a mall filled with hundreds of stalls selling nothing but tablets. I walked into the middle of the scrum to a random stall. I pointed to one of the devices on display and asked, “How much for this one?” 300 kuai. My Mandarin is a bit rusty, so I had to ask again. Slowly, the stall owner repeated renminbi 300 yuan.
If this were a movie, the lights would have dimmed and all the activity in the room frozen. 300 renminbi is US $ 45. And that was the initial offer price given to a bewildered foreigner in China, no haggling. I felt a literal shock.
I bought the device and did some more research. This was a 7-inch tablet, Wi-Fi only with all the attributes of a good tablet. Capacitive touchscreen. Snappy processor. Front facing camera. 4GB of internal memory and an expandable memory slot.
I later found out that these devices are now all over the supply chain in Shenzhen. At volume, say 20,000 units, you can get them for $35 apiece. My device ran full Android 4.0 Ice Cream Sandwich and had access to the full Google API, including Gmail, Maps, YouTube and Google Play (not quite sure how that works either).
Once my heart started beating again, the first thing I thought was, “I thought the screen alone would cost more than $45.” My next thought was, “This is really bad news for anyone who makes computing hardware.”
Digital sharecroppers, unite!
By putting the means of production into the hands of the masses but withholding from those same masses any ownership over the product of their work, Web 2.0 provides an incredibly efficient mechanism to harvest the economic value of the free labor provided by the very, very many and concentrate it into the hands of the very, very few. —writer Nicholas Carr
Well done.Nonc Hilaire wrote:Dropped my old iPhone into the toilet Monday and went to pick up a new one at the Apple Store today.
Seems it was delivery day for the new smaller iPad. The salesperson turned a delightful shade of fuscia when I asked her if she preferred the mini pad or the maxi pad.
what makes you say that ?Enki wrote:One advantage of the Windows tablets and phones is they are not data mining your contacts like Google and Apple.
Thanks for the info.Sparky wrote:Samsung / ASUS rule the roost, but for bang for buck, I can recommend looking at the Toshiba AT 300 (I think it's called the excite in the US)
+:
It's reasonably priced.
It's got a decent screen, speakers and battery life.
It's got a Tegra 3 quad core + one watchdog core processor, so it copes well with tasks ranging from bonsai to Banzai!!!
It comes with an unmolested copy of Android 4 and only a minimal amount of bloatware - all of which can be uninstalled.
-:
The cameras are mediocre at best.
Not rootable (yet).