Death Wish

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Something I’ve Never Thought About Before

they tore down my childhood home in istanbul. i visited last winter break and saw this nine foot statue in its place

Caillou is coming for you

Caillou destroys a neighborhood and gets grounded

The magic was in YOU.

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Knowledge interconnected.

I stumbled upon some of this drawings and I’ve compiled some of them. Apparently they originated here in Tumblr:

keep at it, Brain

Why must we play god

Artistic Style Transfer For Videos

Graphics research from the University of Freiburg Computer Vision group have adapted the artistic Style Transfer method for video / moving image to great effect:

The research paper can be found here

More Cluster Fudge HERE

parents: why don’t you do anything me: minimalism

(via yakmo)

What You See Is What You Get

Promo for augmented glasses product Meta provides convincing demonstration of their technology through perspective of eyewear:

Link

I APPROVE OF THIS LEVEL OF NERDY ANARCHISM

@willylordofnothing

ok that’s pretty cool

Anarchist geometry test. No gods, no rulers.

ANARCHY!

Microscope Uses Artificial Intelligence to Find Cancer Cells

A microscope, invented by a professor at the University of California, uses artificial intelligence in order to locate cancer cells more efficiently than ever before. The device uses photonic time stretch and deep learning to analyze 36 million images every second without damaging the blood samples. This new technique for identifying problematic cells is faster and more accurate than standard methods currently in practice.

Commonly, doctors will add biochemicals to blood samples in order to check for cells containing cancer. The biochemicals attach what scientists call “biological labels” to damaged cells, which enables instruments to both locate and identify differences. These tests have proven problematic, as the biochemicals used would often damage cells, making them unusable for future testing. Other techniques currently in practice do not label cells, but identify cancer cells based on physical characteristics that can oftentimes falsely identify regular cells as damaged.

The photonic time stretch microscope images cells without causing them harm and can identify over two dozen physical characteristics, including: biomass, granularity and size. This alone makes for much more accurate and effective identification of the correct cells and makes retesting an option that wasn’t always available in the past. These new tests invented at UCLA use a photonic time stretch microscope, a practice capable of imaging cells in blood samples very quickly. Couple that with a deep learning computer program that locates cancer cells correctly 95% of the time, and you have a much better chance of pinpointing cancer cells early on, allowing for quicker treatment to stop the spread. Deep learning is a popularly used artificial intelligence that works with complex algorithms to pull meaning from data, leading to better decision making.

The most recent studies lead by Barham Jalali, professor and Northrop-Grumman OptoelectronicsChair in electrical engineering; Claire Lifan Chen, a UCLA doctoral student; and Ata Mahjoubfar, a UCLA postdoctoral student were published in the journal, Nature Scientific Reports. Jalali invented photonic time stretch. This new technology can prove to be helpful in many different scientific applications. For now, the main focus is its ability to take pictures of blood cells with the help of flashing lasers. The lasers can be compared to the flash of a camera and occur in a matter of nanoseconds, something normal instrumentation would not be able to digitize. With the help of optics that boost clarity within images while at the same time slowing them down just enough to detect and capture at a rate of 36 million images each second, the new microscope can track information not possible in the past. The deep learning function then distinguishes the difference between healthy and cancer riddled white blood cells.

Mahjoubfar says each frame is slowed down in real time and then amplified on an optical level so the data can be rapidly digitized. This lets scientists perform fast cell imaging that artificial intelligence is then able to classify. Chen states the photonic time stretch approach allows researchers to identify rogue cells in a very short period of time even with low levels of illumination.

UCLA researchers added in their latest paper that the system could expedite the availability of new treatments for disease because of their data-driven diagnoses. Physical characteristics of cells would help reach cancer diagnoses much faster than ever before. This new technology will also lead to a better understanding of tumor specific genes within cells.

This is a jar full of major characters 

Actually it is a jar full of chocolate covered raisins on top of a dirty TV tray. But pretend the raisins are interesting and well rounded fictional characters with significant roles in their stories. 

We’re sharing these raisins at a party for Western Storytelling, so we get out two bowls. 

Then we start filling the bowls. And at first we only fill the one on the left. 

This doesn’t last forever though. Eventually we do start putting raisins in the bowl on the right. But for every raisin we put in the bowl on the right, we just keep adding to the bowl on the left. 

And the thing about these bowls is, they don’t ever reset. We don’t get to empty them and start over. While we might lose some raisins to lost records or the stories becoming unpopular, but we never get to just restart. So even when we start putting raisins in the bowl on the right, we’re still way behind from the bowl on the left. 

And time goes on and the bowl on the left gets raisins much faster than the bowl on the right. 

Until these are the bowls. 

Now you get to move and distribute more raisins. You can add raisins or take away raisins entirely, or you can move them from one bowl to the other. 

This is the bowl on the left. I might have changed the number of raisins from one picture to the next. Can you tell me, did I add or remove raisins? How many? Did I leave the number the same?

You can’t tell for certain, can you? Adding or removing a raisin over here doesn’t seem to make much of a change to this bowl. 

This is the bowl on the right. I might have changed the number of raisins from one picture to the next. Can you tell me, did I add or remove raisins? How many? Did I leave the number the same?

When there are so few raisins to start, any change made is really easy to spot, and makes a really significant difference. 

This is why it is bad, even despicable, to take a character who was originally a character of color and make them white. But why it can be positive to take a character who was originally white and make them a character of color.

The white characters bowl is already so full that any change in number is almost meaningless (and is bound to be undone in mere minutes anyway, with the amount of new story creation going on), while the characters of color bowl changes hugely with each addition or subtraction, and any subtraction is a major loss. 

This is also something to take in consideration when creating new characters. When you create a white character you have already, by the context of the larger culture, created a character with at least one feature that is not going to make a difference to the narratives at large. But every time you create a new character of color, you are changing something in our world. 

I mean, imagine your party guests arrive

Oh my god they are adorable!

And they see their bowls

But before you hand them out you look right into the little black girls’s eyes and take two of her seven raisins and put them in the little white girl’s bowl.

I think she’d be totally justified in crying or leaving and yelling at you. Because how could you do that to a little girl? You were already giving the white girl so much more, and her so little, why would you do that? How could you justify yourself?

But on the other hand if you took two raisins from the white girl’s bowl and moved them over to the black girl’s bowl and the white girl looked at her bowl still full to the brim and decided your moving those raisins was unfair and she stomped and cried and yelled, well then she is a spoiled and entitled brat. 

And if you are adding new raisins, it seems more important to add them to the bowl on the right. I mean, even if we added the both bowls at the same speed from now on (and we don’t) it would still take a long time before the numbers got big enough to make the difference we’ve already established insignificant. 

And that’s the difference between whitewashing POC characters and making previously white characters POC. And that’s why every time a character’s race is ambiguous and we make them white, we’ve lost an opportunity.

*goes off to eat her chocolate covered raisins, which are no longer metaphors just snacks*

The Others

Visual short by Hiroshi Kondo applies time-based motion effects on footage of busy pedestrian traffic crossing:

More Here

Hiroshi also has a tumblr blog [@stnw] here