The art-form sensation known as “Simpson Vapourwave”
A combination of various The Simpsons clips with a mix of vapourwave visuals, sounds and songs. This video being one of my favorites of them.
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PELEPE Rail
10 DecIsraeli poet and artist Ave has been a regular feature onthe DPV since it’s very beginning. Ave’s video (see here) are unique in that what makes them psychedelic is not a garish flow of colors on the screen, but rather something more simple and unmediated. The felt presence of immediate experience.
Whether it is two plastic bags hovering around each other in the wind like two lovers caught up in a dance, or a zen moment on top of an amusement park merry go round, Ave’s videos capture something elusive and beautiful about the reality of the present moment. As a viewer, you tend to get caught in the experience of what is happened in those very moments in which the video was shot.
Ave has a very Zen-like approach to film making, a way of filming reality and yet being present in it. Whether he is the one shooting the video or the one to appear in it, the camera is not invisible. It is part of the scene, like a participator but in a way that doesn’t hem or hamper the magic which happens on the screen but ends up making it even brighter and more awesome.
Ave’s present video, Pelepe, is, to my mind, his best work so far. It starts as a regular ride on the Israel train service, but then Ave and his partner in this video, the dancer K, begin their highly peculiar act which is difficult to describe: is this a dance? a performance? a meditation?
As they continue they arouse the interest of not only their immediate wagon neighbors. The entire train car gets involved, all sharing the magic of the moment, the wonder of watching people open up like this, sharing their intimacy with strangers on the train. In this way, Ave and K give those around them the present of intimacy, as the whole train wagon gets immersed in the special and beautiful happening.
Things continue to evolve from there, ending with a reminder of the kind of fears this intimacy and expressiveness can also stimulate in some, and the existence of violence which is always there lurking alongside the beauty and the joy in this imperfectly perfect world of ours.
A spectacular video.
Acro Flashmob
16 AprA flash mob of acro-balance artists takes Tel Aviv passerby crowd by surprise, as more and more join the party.
Journey through the layers of the mind // Memo Akten
8 JulA visualisation of what’s happening inside the mind of an artificial neural network.
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).
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
Babies going through tunnels
12 JunThese babies reactions to the experience of going through a tunnel are so sweet and psychedelic. It’s like they’re going “Whooo! What was that?!!!”. And maybe we should always be like that when going through tunnels. People say babies are in a constant trip. This brings the point home.
(Link: Hagai. Thanks!)
