24 January 2016
23 January 2016
11 January 2016
Nitrous and Valium
Pruno (Prison wine)
It’s a topic that’s inspired endless debate—the link between art and creativity and brain-altering chemicals. Usually, the drugs are a lifestyle choice of "creative" types. In the case of artist Bryan Lewis Saunders, they were a key part of the process and end product.
Saunders, a performance and visual artist, undertook a high profile experiment in creativity, starting several years ago whereby, according to the artist, he created a series of self-portraits, each one done under the influence of a different substance—pretty much an A to Z assortment, from prescription meds like Abilify and Xanax to crystal meth. Over the weeks he’d create amazing pieces, suffer mild brain damage and end up hospitalized—all for the sake of art and creation.
... While this was all done in the name of art, Saunders is quick to say that the drug use is nothing to be proud of. "To be honest I’m not proud to be on any drugs in any pictures. I think drugs make me look really ugly. And I’m really a six trick pony, but the world only likes one of my tricks. Each year 500,000 kids around the world discover drugs and so the virus never dies." Saunders, who started creating a self-portrait a day in 1995, has done over 8,600 self-portraits ...More at FastCoCreate | Bryan Lewis Saunders
09 January 2016
In the United States, close to 10 percent of the population struggles with depression, but sometimes it can take a long time for someone to even understand that they are suffering. One difficulty in diagnosis is trying to distinguish between feeling down and experiencing clinical depression.
A new TED-Ed video can help someone make the distinction. With simple animation, the video explains how clinical depression lasts longer than two weeks, with a range of symptoms that can include changes in appetite, poor concentration, restlessness, sleep disorders (either too much or too little), and suicidal ideation. The video briefly discusses the neuroscience behind the illness, outlines treatments, and offers advice on how you can help a friend or loved one who may have depression.
Unlike the many pharmaceutical ads out there with their cute mascots and vague symptoms, the video uses animation to provide clarity about the mental disorder. It’s similar in its poignant simplicity to the HBO short documentary, “My Depression,” based on Liz Swados’s book of the same name.GOOD Magazine | TED-Ed on YouTube
04 January 2016
This is a severely excerpted selection from an open letter by Craig Malkin, a psychologist who studies narcissism. The original letter was posted online in Psychology Today.
... As an expert on narcissism, I'm not especially worried that narcissists might make it to the White House. According to research, they've always been there. And that shouldn't scare us anyway, because, just to be clear: Being a narcissist is not a diagnosis. It never has been. Narcissists are people higher in narcissistic traits than the average person, and while they may or may not be disordered, they all share one thing in common: They feel special. Some feel special enough to lead a nation, in fact. What we should be far more concerned about is not whether politicians are narcissists -- most are -- but how healthy they are.Learn more at Dr. Malkin's FB page.
... Politicians are groomed by us -- by our applause, by our polls, by our votes. Whatever you seem to love or hate, they'll embrace or reject. So be careful what you applaud or attack. It matters what they-- and all the little future leaders watching them -- think you want in a leader.
- Do applaud careful reflection.
- Don't applaud insults.
- Do applaud feelings.
- Don't applaud manipulation.
- Do applaud collaborative behavior.
- Don't applaud black-and-white thinking.
- Do applaud apologies.
- Don't applaud evasiveness.
- Do applaud curiosity.
02 January 2016
The Dictionary of Obscure Sorrows is a compendium of invented words written by John Koenig. Each original definition aims to fill a hole in the language—to give a name to emotions we all might experience but don’t yet have a word for ... Watch the YouTube Series, with new episodes every other Sunday.More here
01 January 2016
25 December 2015
26 November 2015
Like so many other crickets, a Roesel’s bush cricket sings to attract his mate. But his courtship doesn’t stop once a female finds him. As they have sex he’ll use a pair of tiny drumsticks on his genitals to show her he’s the rhythm master she wants to father her young. The structures are called titillators; they’re small stiff rods that sit at the base of the penis and are inserted into a female during sex ...
The drumming seems to be an important sexual step for this cricket. Females often tried to stop mating with males whose titillators had been removed–especially in the males who were left with only one drumstick. And even when the females put up with their rhythm-impaired mates, the males were less successful in getting their sperm to stick.Read the rest of the story here.
25 November 2015
05 September 2015
20 August 2015
07 August 2015
30 July 2015
Made with Blender, Gimp, Octane and Natron. Thanks to Blackschmoll, Boby, Christophe, Clouclou, Cremuss, David, Félicia, Frenchman, Sozap, Stéphane, Virgil. And Thanks to Ton Roosendaal, the Blender community, the developers of Blender, Gimp and Natron.Music by Joe Hisaishi. dono 2015
21 July 2015
07 July 2015
05 July 2015
From the description on Vimeo:
A visualization of what's happening inside the mind of an artificial neural network.
By recognizing forms in these images, your mind is already reflecting what's going on in the software, projecting its own bias onto what it sees. You think you are seeing things, perhaps puppies, slugs, birds, reptiles etc. If you look carefully, that's not what's in there. But those are the closest things your mind can match to what it's seeing. Your mind is struggling to put together images based on what you know. And that's exactly what's happening in the software. And you've been training your mind for years, probably decades. These neural networks are usually trained for a few hours, days or weeks.
In non-technical speak:
An artificial neural network can be thought of as analogous to a brain (immensely, immensely, immensely simplified. nothing like a brain really). It consists of layers of neurons and connections between neurons. Information is stored in this network as 'weights' (strengths) of connections between neurons. Low layers (i.e. closer to the input, e.g. 'eyes') store (and recognise) low level abstract features (corners, edges, orientations etc.) and higher layers store (and recognise) higher level features. This is analogous to how information is stored in the mammalian cerebral cortex (e.g. our brain).
Here a neural network has been 'trained' on millions of images - i.e. the images have been fed into the network, and the network has 'learnt' about them (establishes weights / strengths for each neuron). (NB. This is a specific database of images fed into the network known as ImageNet http://image-net.org/explore )
Then when the network is fed a new unknown image (e.g. me), it tries to make sense of (i.e. recognise) this new image in context of what it already knows, i.e. what it's already been trained on.
This can be thought of as asking the network "Based on what you've seen / what you know, what do you think this is?", and is analogous to you recognising objects in clouds or ink / rorschach tests etc.
The effect is further exaggerated by encouraging the algorithm to generate an image of what it 'thinks' it is seeing, and feeding that image back into the input. Then it's asked to reevaluate, creating a positive feedback loop, reinforcing the biased misinterpretation.
This is like asking you to draw what you think you see in the clouds, and then asking you to look at your drawing and draw what you think you are seeing in your drawing etc,
That last sentence was actually not fully accurate. It would be accurate, if instead of asking you to draw what you think you saw in the clouds, we scanned your brain, looked at a particular group of neurons, reconstructed an image based on the firing patterns of those neurons, based on the in-between representational states in your brain, and gave *that* image to you to look at. Then you would try to make sense of (i.e. recognise) *that* image, and the whole process will be repeated.
We aren't actually asking the system what it thinks the image is, we're extracting the image from somewhere inside the network. From any one of the layers. Since different layers store different levels of abstraction and detail, picking different layers to generate the 'internal picture' hi-lights different features.
All based on the google research by Alexander Mordvintsev, Software Engineer, Christopher Olah, Software Engineering Intern and Mike Tyka, Software Engineer