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I finally finished rendering the bigger version of the "wasp nest". I rendered it during the day and at night I switched the pc to standby. But the rendering time is still incredible: 712:04:58.8
That's about 30 days... but it was worth it ;)
This project is part of the CyberArts 2020 exhibition at the OK.
This multisensory project calls into question the concept of mass production by envisioning a potential future personalized perfumery. The Algorithmic Perfumery evaluates completed customer questionnaires and uses the data to generate a unique scent. The respondents’ feedback on this personal perfume is then in turn fed back into the program to refine the compositions developed by the algorithm. By interacting with the machine, users are given the power to play an active role in the creative process: the machine learns from their personal physical experiences and subjective (olfactory) sensations.
For more information please visit:
ars.electronica.art/keplersgardens/en/prix-interactive-art/
Credit: vog.photo
I think the shuffling pattern determines the frequency of transitions for a given bit. So far I've been using bit-order inversion (0xAC => 0x35) to shuffle bits. But I think something that moves bits in one area more and bits in another area less will give me a more useful distribution (rather than resembling white noise).
Basically, I've made a pseudorandom number generator for arbitrary bit lengths that has a perfect period, but it acts too much like white noise.
Colorized by Artificial Intelligence Algorithm Tool from originally scanned hi-res photo from the respective source.
Credit disclaimer: I do not own the original scanned image and believe that it is in the public domain. These images have been collected from Flickr's search results and/or collected from various internet sources. If you know the link to the original image, please kindly put it into comment section as I will update the description to give full credit to the respective owner.
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Algorithmically generated image created entirely from random numbers run through mathematical equations.
A collaboration with onformative.com. A pixelrow of a photograph is taken and then sorted by colorvalues. Done with processing.
ALGO 2017 hosted by Algorithms and Complexity Group of TU Wien, 4-8 September. Official photography: Nadja Meister. The photos have been released under CC BY 4.0.
Variations in pattern development through scripting, also some more general explorations in geometry and part to whole relationships
I'm thrilled. A computer algorithm has chosen exactly 100 of my photos to be in the club known as explore. This would not be a big deal, but I love that number 100, and it does make such a nice square.
The 100th photo is a picture of hot air.
My most viewed photo is not part of the collection.
My most "Interesting" photo is not part of the collection.
And I don't choose favorites among my shots.
See them here, without clicking on the disorganized links that Big Huge Labs supplies. (And I can't figure out which one is missing from this search!)
Algorithmic art created with Processing using blue noise dot patterns, wave functions, and various other computational techniques.
I keep telling myself it's time to retool this generative system--use functions more complicated than simple sine waves, different shapes--but when I set out to retool, I discover aspects I hadn't yet explored.
The series Sturdy, Rendition, Fuste, Eyeteeth, and Elpenor do use many more points than earlier images. Voluntad (like Chupatintas and a few others) uses different color rules. Otherwise, these are all variations on a basic generative system.
See www.openprocessing.org/visuals/?visualID=15891 for code used to generate "dot pattern" images.
Variations in pattern development through scripting, also some more general explorations in geometry and part to whole relationships
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Algorithmes Sérigraphiques
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Day 4 and we have started printing, yeah !
Algorithmes Sérigraphiques is a week long creative workshop using Processing to generate images and silk screen to print the results.
Un workshop d'une semaine avec du Processing et de la sérigraphie.
For further info/Plus d'infos : www.freeartbureau.org/blog/
Colorized by Artificial Intelligence Algorithm Tool from originally scanned hi-res photo from the respective source.
Credit disclaimer: I do not own the original scanned image and believe that it is in the public domain. These images have been collected from Flickr's search results and/or collected from various internet sources. If you know the link to the original image, please kindly put it into comment section as I will update the description to give full credit to the respective owner.
Please follow, like and leave a comment for more exiting future notifications.
My websites:
Visit my portfolio sites:
www.saatchiart.com/celestialart
www.redbubble.com/people/Motionage/shop
FOLLOW ME:
www.youtube.com/channel/UC8JtcV_EejccsUNXSK_ejcw Springs of Eden
Colorized by Artificial Intelligence Algorithm Tool from originally scanned hi-res photo from the respective source.
Credit disclaimer: I do not own the original scanned image and believe that it is in the public domain. These images have been collected from Flickr's search results and/or collected from various internet sources. If you know the link to the original image, please kindly put it into comment section as I will update the description to give full credit to the respective owner.
Please follow, like and leave a comment for more exiting future notifications.
My websites:
Visit my portfolio sites:
www.saatchiart.com/celestialart
www.redbubble.com/people/Motionage/shop
FOLLOW ME:
www.youtube.com/channel/UC8JtcV_EejccsUNXSK_ejcw Springs of Eden
Panel Algorithmic Business Strategies - If everything's being uploaded and shared, what might be next?
Moderator - Mercedes Bunz
Speaker - Dirk Baecker, Jean-Paul Schmetz, - Sean Park, Tom Fuerstner
Wilkinson Eyre's egg was bathed in light that cycled through the spectrum. Here it is bathed in red.
The steady advancement of artificial intelligence is rapidly transforming our world with a host of emerging innovations such as self-driving cars, automated financial advisers, and expert medical systems. Developers are producing data-intensive computer systems designed to observe, learn, and solve complex problems faster and more accurately than their human counterparts. As these technologies become increasingly mainstream, they promise enormous public benefits including higher productivity, improved health and safety, and fairer decision making. While these technologies have incredible potential to generate economic and social good, these breakthroughs may not occur unless the public and private sectors work in partnership to promote the development and adoption of artificial intelligence, address new regulatory questions, and integrate the technology into agencies at all levels of government.
The Center for Data Innovation hosted a conversation with leading experts on the state of artificial intelligence and machine learning, the efforts by the public and private sectors to support related research and development, and the important policy steps that regulators and lawmakers should make to unlock these new opportunities.
Speakers included: Greg Corrado (co-lead of Google’s deep neural networks project), Ashley J. Llorens (Chief of the Intelligent Systems Center at the Johns Hopkins University Applied Physics Laboratory), Fernando Diaz (Senior Researcher at Microsoft Research), Dennis Mortensen (CEO, x.ai), FTC Commissioner Terrell McSweeny, Terah Lyons (Policy Advisor, Office of Science and Technology Policy, White House), Hilary Cain (Director, Tech and Innovation Policy, Toyota), and David Moschella (Director of Research, Computer Sciences Corp).
A collaboration with onformative.com. A pixelrow of a photograph is taken and then sorted by colorvalues. Done with processing.
This is three runs of Wolfram's "Rule 110" cellular automaton. Each run is assigned to a color channel - R, G, and B. Each color began with two pixels turned "on": one in the upper middle, and one that they all shared in the upper right. The sum of all the channels maxes out at 255, so pixels with more colors turned on have a lower intensity. This helps the interference patterns become more apparent. I really like how the encounters propagate backwards when a color hits the uniform white section.
Code is here, I put it in a file called GOL.py and typed: python GOL.py > p.ppm && convert p.ppm p.png