10th April 2012

Photo reblogged from Miss Aqua with 270 notes

romanjaimeson:

rope in bed…♥

romanjaimeson:

rope in bed…♥

Source: fettish

5th February 2012

Post reblogged from Free tickets to Hell, here! with 1,852,290 notes

Reblog if you are God.

Source: monsterscontrolmysoul

4th February 2012

Photo reblogged from breathingcorpses. with 395 notes

such choices where should i start….

such choices where should i start….

Source: angelasmassacre

4th February 2012

Photo reblogged from Free tickets to Hell, here! with 523 notes

HOLE IN ONE!!!!!

HOLE IN ONE!!!!!

Source: alackofoxygen

4th February 2012

Photo reblogged from Free tickets to Hell, here! with 2,298 notes

Source: vetonimia

4th February 2012

Photo reblogged from Free tickets to Hell, here! with 212 notes

Source: elwood-ziggurat

3rd February 2012

Photo reblogged from Miss Aqua with 1,233 notes

Source: wphotography.deviantart.com

3rd February 2012

Photo reblogged from breathingcorpses. with 697 notes

whoa

whoa

Source: anxieties

3rd February 2012

Photo reblogged from breathingcorpses. with 100 notes

hi my name’s rich

hi my name’s rich

Source: existential-outrage

2nd February 2012

Photo reblogged from Kinky, Creepy, Cute. with 81 notes

1st February 2012

Photo reblogged from crooked indifference with 798 notes

crookedindifference:

The “Most Important Algorithm Of Our Lifetime” Could Change This Modern World

Math breakthroughs don’t often capture the headlines—but MIT researchers have just made one that could lead to all sorts of amazing technological breakthroughs that in just a few years will touch every hour of your life.
Here’s a quickie explainer: Fourier transforms are a mathematical trick to simplify how you represent a complicated signal—say the waves of sound made by speaking. They work by reducing the complex wave pattern to a simple and pretty short list of numbers that, when run through the system again, result in a very good approximation of the original signal. FFTs (Fast Fourier Transforms) are simply a way of making this magic happen in a digital computer, but the combination of math and machine means the FFT has revolutionized science and many industries that have technology at their core. Which is why it’s been labeled the “most important algorithm of our lifetime.”
Now, you should remember that sound waves, and both picture and video signals, are all handled by processors in your TV, PC, and phone, and that the radio waves that whizz through the air to keep us all connected to the Internet need digital processing too. That’s every compressed sound signal that you listen to as an MP3 or similar format, most every image that you snap with your smartphone or DSLR, every image frame in the video you’re watching on your TV streamed over the Net, many images—such as those from an MRI—your doctor uses to diagnose your disease and every burst of radio that connects your cell phone to the nearest tower or your PC to its Wi-Fi router. 
So calculating FFTs up to ten times faster is a big deal. It means that if you use existing hardware to do the math, it’ll be quicker at solving the problem you’ve set—so you need less compute time to do the task. If you’re talking about a portable computer like the one in your smartphone, that means it can spend more time doing other things instead. And with the valuable computing and battery resources of these portable devices under such pressure (you wouldn’t want your phone to be laggy now, would you?) that’s a good thing.

crookedindifference:

The “Most Important Algorithm Of Our Lifetime” Could Change This Modern World

Math breakthroughs don’t often capture the headlines—but MIT researchers have just made one that could lead to all sorts of amazing technological breakthroughs that in just a few years will touch every hour of your life.

Here’s a quickie explainer: Fourier transforms are a mathematical trick to simplify how you represent a complicated signal—say the waves of sound made by speaking. They work by reducing the complex wave pattern to a simple and pretty short list of numbers that, when run through the system again, result in a very good approximation of the original signal. FFTs (Fast Fourier Transforms) are simply a way of making this magic happen in a digital computer, but the combination of math and machine means the FFT has revolutionized science and many industries that have technology at their core. Which is why it’s been labeled the “most important algorithm of our lifetime.”

Now, you should remember that sound waves, and both picture and video signals, are all handled by processors in your TV, PC, and phone, and that the radio waves that whizz through the air to keep us all connected to the Internet need digital processing too. That’s every compressed sound signal that you listen to as an MP3 or similar format, most every image that you snap with your smartphone or DSLR, every image frame in the video you’re watching on your TV streamed over the Net, many images—such as those from an MRI—your doctor uses to diagnose your disease and every burst of radio that connects your cell phone to the nearest tower or your PC to its Wi-Fi router. 

So calculating FFTs up to ten times faster is a big deal. It means that if you use existing hardware to do the math, it’ll be quicker at solving the problem you’ve set—so you need less compute time to do the task. If you’re talking about a portable computer like the one in your smartphone, that means it can spend more time doing other things instead. And with the valuable computing and battery resources of these portable devices under such pressure (you wouldn’t want your phone to be laggy now, would you?) that’s a good thing.

Source: Fast Company

1st February 2012

Photo reblogged from breathingcorpses. with 356 notes

my new house

my new house

Source: balidora

1st February 2012

Photoset reblogged from Miss Aqua with 2,453 notes

fuckyeahillustrativeart:

Tobias Kwan

Source: fuckyeahillustrativeart

1st February 2012

Photo reblogged from breathingcorpses. with 79 notes

Source: l1zarruda

1st February 2012

Photo reblogged from Miss Aqua with 2 notes

Source: the-ecstasy-1368