How Crypto Artists are Using AI to Scale and Augment Creative Processes

How Crypto Artists are Using AI to Scale and Augment Creative Processes

Dec 8, 2020 Artist Statements

Above: “data privacy” by stockcatalog licensed under CC BY-SA 2.0

How Crypto Artists are Using AI to Scale and Augment Creative Processes

SuperRare
3 years ago

Editorial is open for submissions: [email protected]

by Playform.io

Sample of shared users images at Playform.io

We developed Playform as an AI Art studio to allow artists to experiment and explore the use of generative AI as part of their creative process. Our goal is to make AI accessible to artists, realizing several challenges that face artists and creatives when approaching this technology. Now with the advent of Cryptocurrency and the expansion of the Crypto art world, artists and creators are using Playform technology to evolve a new kind of art.

With Artificial Intelligence (AI) becoming incorporated into more aspects of our daily lives, from our phones to driving, it’s only natural that artists would also start to experiment with artificial intelligence. However, this is not new. Since the dawn of AI, over the last 50 years, several artists have explored with computer programs to generate art, incorporating intelligent elements in some cases. The most prominent early example of such work is by Harold Cohen and his art-making program AARON, which produced drawings that followed a set of rules Cohen had hard-coded. American artist Lillian Schwartz, a pioneer in using computer graphics in art, also experimented with AI, among others.

But AI has emerged over the past couple of decades and incorporated machine learning technology. This resulted in a new wave of algorithmic art that uses AI in new ways to make art in the last few years. In contrast to traditional algorithmic art, in which the artist had to write detailed code that already specified the rules for the desired aesthetics, in this new wave the algorithms are set up by the artists to “learn” the aesthetics by looking at many images using machine learning technology. The algorithm only then generates new images that follow the aesthetics it has learned.

The most widely used tool for this is Generative Adversarial Networks (GANs), introduced by Goodfellow in 2014 (Goodfellow 2014), which has been successful in many applications in the AI community. It is the development of GANs that has likely sparked this new wave of AI Art.

However, using GAN-like generative methods in making art is challenging and beyond the reach of the majority of artists, except for creative technologists. I will try to summarize these challenges here.

GAN-Ocean: In the last few years, since the introductions of GAN, there has been explosive interest in the AI community in developing new types of improved GANs, addressing several of its limitations and extending its capabilities as a generative engine for images, language, and music. This makes it impossible for an artist trying to approach this technology to even know where to start. For example, going to the code repository Github, where developers deposit their open source codes, if you search for the term “GAN”, you are destined to find several tens of thousands of GAN variants available. As an artist, you were left clueless in front of this ocean of GAN-like algorithms, wondering where to start and which algorithm would fit your creative process.

Screen shot of code repository GitHub showing over than 33K available open source codes for GAN variants. (screen shot taken in April 2020)

Computational challenge: Even with the availability of open-source codes, several challenges will face artists. If you are not a code developer who is familiar with today’s programming languages and up to date with latest AI libraries, it is very unlikely that you would be able to benefit from existing open-source codes. Moreover, running such sophisticated AI programs requires the availability of GPUs (Graphical Processing Units), specialized hardware boards that accelerate the processing of multiple folds (10 to 100s folds) to make it possible to train AI models in hours or days instead of several weeks. The price of a GPU board that is able to run state-of-the-art AI algorithms ranges at more than $2,000. Some platforms allow users to use cloud-based GPUs to run open-source codes easily, with hourly charges that can accumulate easily to a substantial bill, if you don’t know what you’re doing.

Massive data requirements: Another challenge that face artists when using GAN-like algorithms is that they require huge amounts of images (tens of thousands) for “training” to get reasonable results. Most of these algorithms are trained and tested on available image datasets, typically curated and catered for AI research. Instead, most artists would like to use their own image collections in their projects. At Playform, we found that in most cases artists want to train AI algorithms with collections of less than 100 images. This small number of images will not be sufficient to train off-the-shelf AI algorithms to generate desired results.

The Terminology Barrier: As a non-AI expert, you will be faced with a vast number of technical terms that you will need to navigate through to get the minimum understanding needed to be in control of the process. You will have to understand concepts like: training, loss, over-fitting, mode collapse, layers, learning rate, kernels, channels, iterations, batch size, and lots and lots of other AI jargons. Most artists would give up here, or blindly, play around with the knobs hoping to get interesting results to realize that you are more likely to win the lottery. Given the cost of GPU time and the lengthy process, that would mean hours and hours of wasted time and resources without getting anything interesting.

Introducing Playform:

We built Playform to make AI accessible for artists. We want artists to be able to explore and experiment with AI as part of their own creative process, without worrying about AI terminology, or the need to navigate unguided through the vast ocean of AI and GAN-like algorithms.

Most generative-AI algorithms are mainly developed by AI researchers in academia and big corporate research labs to push the technology boundary. Artists and creatives are not typically the target audience when these algorithms are developed. The use of these algorithms as part of an artist’s work is an act of creativity by the artist who has to be imaginative in how to bend, adopt, and utilize such non-specialized tools to their purpose. In contrast, Playform focused on how to build AI that can fit the creative process of different artists, from the stage of looking for inspiration, to preparation of assets, all the way to producing final works.

At the research and development side, we had to address the problem that GANs require a large number of images and long hours of training. We had to work on developed optimized versions of GANs that can be trained with tens of images, instead of thousands, and can produce reasonable results in a matter of one or two hours.

Workflow in Playform. User chooses a creative process (Top Left). User then upload inspiration images and possible influences (Bottom Left). As the training progresses, user sees and navigates through results

At the design side, we focused on making the user experience intuitive and free of AI jargon. All the AI is hidden under the hood. Users choose a creative process, upload their own images and press a button to start training. Within minutes results will start to pop up and evolve as the training continues. Within an hour, or a bit more, the process is done and you have already generated thousands of images. Users can navigate through all iterations to find their favorite results. Users can also continue the training process as needed to achieve better results.

What SuperRare Artists have done using Playform

Some artists used Playform as a mean of looking for inspirations based on AI uncanny aesthetics. Some other artists fed images of their own artworks, training models that learn their own style and then used these models to generate new artworks based on new inspirations. Virtual reality artists used AI to generate digital assets to be integrated in virtual reality experiences. Several artists used Playform to generate imagery that were used in creating videos. Playform was also used to generate works that were upscaled and printed as a final art product.

SuperRare user and Playform artist Travis LeRoy Southworth (@travisleroy) integrated Playform AI inputting hundreds of past works as a data set to create what the artist refers to as “digital blemishes and color adjustments to construct new portraits.” The result of the inputs transform into surrealist and dream-like figures, featured from his series titled “New Beginnings, Old Endings, Secrets Secreting,” on SuperRare. “I use the Playform GAN to explore alternative methods of art creation and digital outsourcing,” LeRoy writes on the exhibition process. The artist’s past work is used to “train the machine in my paintings’ style,” which is then fed into Playform. The process continues beyond Playform into Photoshop and After Effects where LeRoy animates and “gives life” to Playform outputs. The New York City based artist presented these works using Playform on Artsy in October, 2020. 

(Travis LeRoy, Left to right: Sixer, The Watcher (Clown Cloud #1,)  from the series “New Beginnings, Old Endings, Secrets Secreting,” with Playform AI, 2020)

SuperRare artist @coldie uses Playform capabilities in GANdinsky 3D – Green and Red – Variant 01, inputting Wassily Kandinsky’s original Image with Arrow into AI generation. “Kandinsky is one of my favorite artists of all time and it is an honor to work with his art in a new way using technology not available during his era,” the artist says of the AI process juxtaposed with traditional Kandsinsky content.

(Coldie, GANdinsky 3D – Green and Red – Variant 01, with Playform AI, 2020)

Mattia Cuttini, the current Playform artist in residence, is an Italian artist whose interdisciplinary practice is situated at the intersection of graphic design and blockchain technology. At the forefront of Crypto art, Cuttini expands his body of work using Playform AI capabilities. As part of his residency with Playform,  the artist is experimenting with rubber stamps and inks on hundreds of papers, which are then fed into Playform’s AI. Cuttini looks for technological error and glitch, challenging the AI’s aim for replication. 

(Mattia Cuttini, Undefined #5, Using Playform AI, 2020)

(Mattia Cuttini, Undefined #6, Using Playform AI, 2020)

Mattia Cuttini will be hosting an Artist Talk on Tuesday, December 15, 2020, to discuss how he used Playform in his most recent series of work and his personal experiences navigating the crypto art market. Attendees will get an additional 5 Playform credits ($25 value). You can register for the event at playform.io/superrare. 

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SuperRare

SuperRare is a marketplace to collect and trade unique, single-edition digital artworks.

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Curators' Choice

Helena Sarin: Celebrating the original GANcomic

Helena Sarin: Celebrating the original GANcomic

Oct 29, 2020 Uncategorized

Editorial is open for submissions: [email protected]

by Sofia Garcia (founder of ARTXCODE)

Helena Sarin: Celebrating the original GANcomic

SuperRare
3 years ago

I’ve been lucky enough to work with the talented Helena Sarin as both a curator and personal collaborator since 2019. As the lead curator of ARTXCODE, I held the honor of exhibiting her CycleGAN computational collage, *Heads in Heaven*, at our group show When the Computer Made Art. Presented as an edition of 5, the set sold out before the show even began. It was such celebratory moment, but little did we know… She would do it all again.

December 2020 will mark one year since Sarin independently published and sold all 75 editions of her hilarious, pun-filled, AI-generated art book: The Book of GANesis: Divine Comedy in Tangled Representations. The book is based on a popular series of artworks Sarin posted on Twitter as parody of AI research papers. She decided to coincide the launch of the book with NeurlPS, a major annual conference for the AI research community and it was an instant success. Janelle Shane, the author of bestseller You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It’s Making the World a Weirder Place was quick to joke “The generated images in @glagolista’s book are stunning at print resolution; but why did nobody warn me the book is like 90% machine learning puns?? “

The Book of GANesis by Helena Sarin, page 11

In terms of composition, The Book of GANesis mirrors the design of a graphic novel and in turn introduced a new genre altogether: GANcomics. A GANcomic follows the idea of using AI-generated artwork to steer the narrative of a book and in place of traditional imagery. In this case, Sarin allows her AI models- trained on her own drawings, sketches, and photographs- to steer the narrative of The Book of GANesis. She credits her inclination “to find patterns and meaning in random information” to her role model Lynda Barry. As for a literary theme, the book decidedly parodies religious text, carrying a theological trope Sarin attributes to a well-known quote by Pamala McCorduck, “AI beGAN with the ancient wish to forge the Gods…”

The Book of GANesis by Helena Sarin, page 5

… and so begins The Book of GANesis.

To commemorate the success of Sarin’s Manga Opus, she has tokenized an assemblage of cutouts from soft proof copies of the book and has included a high-res PDF download of The Book of GANesis upon purchase. The book contains 30 pages of original AI artwork and is considered to be one of the first AI-generated art books.

The Book of GANesis, the First Ever AI Artist Book
Edition 1 of 1

This will be the first of three one-of-a-kind posters celebrating the anniversary of The Book of GANesis. You can purchase your poster with high-def PDF download here.

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SuperRare

SuperRare is a marketplace to collect and trade unique, single-edition digital artworks.

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Curators' Choice

An Introduction to Artist Helena Sarin from Artnome

An Introduction to Artist Helena Sarin from Artnome

Sep 6, 2020 Artist Profiles / Events

We are excited to welcome the artist Helena Sarin, known as @Glagolista on SuperRare, to our platform.

An Introduction to Artist Helena Sarin from Artnome

Artnome
4 years ago

Vsual artist and software engineer, Helena Sarin has always been working with cutting edge technologies, first at Bell Labs, designing commercial communication systems, and for the last few years as an independent consultant, developing computer vision software using deep learning. While she has always worked in tech, Helena has been doing commission work in watercolor and pastel as well as in the applied arts like fashion, food and drink styling and photography.
But art and software ran as parallel tracks in her life, all her art being analog… until she discovered GANs (Generative Adversarial Networks). Since then generative models became her primary medium.
She is a frequent speaker at ML/AI conferences, for the past year delivering invited talks at MIT, Library of Congress and Capitol One.
Her artwork was exhibited at AI Art exhibitions in Zurich, Dubai, Oxford, Shanghai and Miami, and was featured in number of publications including the Jan 2020 issue of “Art In America” magazine.

Moda GANstrakta: the admission ticket
Edition 1 of 1
live fashion drawing , GAN chained a little bit
AIArt #GAN #generativeart

With pretty much all of her 2020 exhibitions and talks cancelled or postponed until 2021,

Helena is using this time of lockdown as an opportunity to work on a few artists books, each featuring her AI artwork.

In 2018 art curator and long time SuperRare art collector Jason Bailey published Sarin’s seminal essay “NeuralBricolage” along with his analysis of Sarin’s work his post “Helena Sarin: Why Bigger Isn’t Always Better With GANs And AI Art” on Artnome. The post has now been read tens of thousands of times and Bailey has agreed to share an excerpt from the foreward for that article with SuperRare community below.

AI art using GANs (generative adversarial networks) is new enough that the art world does not understand it well enough to evaluate it. We saw this unfold in 2018 when the French artists’ collective Obvious stumbled into selling their very first AI artwork for $450K at Christie’s.

Many in the AI art community took issue with Christie’s selecting Obvious because they felt there are so many other artists who have been working far longer in the medium and who are more technically and artistically accomplished, artists who have given back to the community and helped to expand the genre. Artists like Helena Sarin.

Chairwoman, Variations on Masters
Edition 1 of 1

Sarin was born in Moscow and went to college for computer science at Moscow Civil Engineering University. She lived in Israel for several years and then settled in the US. While she has always worked in tech, she has moonlighted in the applied arts like fashion and food styling. She has played with marrying her interests in programming and art in the past, even taking a Processing class with Casey Reas, Processing felt a little too much like her day job as a developer. Then two years ago, she landed a gig with a transportation company doing deep learning for object recognition. She used CycleGAN to generate synthetic data sets for her client. Then a light went off and she decided to train CycleGAN with her own photography and artwork.

This is actually a pretty important distinction in AI art made with GANs. With AI art, we often see artists using similar code (CycleGAN, SNGAN, Pix2Pix etc.) and training with similar data sets scraped from the web. This leads to homogeneity and threatens to make AI art a short-lived genre that quickly becomes repetitive and kitsch. But it doesn’t have to be this way. According to Sarin, there are essentially two ways to protect against this if you are an AI artist exploring GANs.

Love at the First Checkpoint
Edition 1 of 1
GANcollage of my original still life drawings
AI #AIart #collage #GAN #generative #generativeart

First, you can race to use the latest technology before others have access to it. This is happening right now with BigGANs. BigGANs produce higher-resolution work, but are too expensive for artists to train using their own images. As a result, much of the BigGAN imagery looks the same regardless of who is creating it. Artists following the path of chasing the latest technology must race to make their stamp before the BigGAN aesthetic is “used up” and a “BiggerGAN” comes along.

Chasing new technology as the way to differentiate your art rewards speed, money, and computing power over creativity. While I find new technology exciting for art, I feel that the use of tech in and of itself never makes an artwork “good” or “bad.” Both Sarin and I share the opinion that the tech cannot be the only interesting aspect of an artwork for it be successful and have staying power.

That Iconic GAN Weaver
Edition 1 of 1
generative model trained on my original drawings
AI #AIArt #GAN #GenerativeArt

The second way artists can protect against homogeneity in AI art is to ignore the computational arms race and focus more on training models using your own hand-crafted data sets. By training GANs on your own artwork, you can be assured that nobody else will come up with the exact same outputs. This later approach is the one taken by Sarin.

Sarin approaches GANs more as an experienced artist would approach any new medium: through lots and lots of experimentation and careful observation. Much of Sarin’s work is modeled on food, flowers, vases, bottles, and other “bricolage,” as she calls it. Working from still lifes is a time-honored approach for artists exploring the potential of new tools and ideas.

Sarin’s still lifes remind me of the early Cubist collage works by Pablo Picasso and Georges Braque. The connection makes sense to me given that GANs function a bit like an early Cubist, fracturing images and recombining elements through “algorithms” to form a completely new perspective.  As with Analytic Cubism, Sarin’s work features a limited color pallet and a flat and shallow picture plane. We can even see the use of lettering in Sarin’s work that looks and feels like the lettering from the newsprint used in the early Cubist collages.

I was not surprised to learn that Sarin is a student of art history. In addition to Cubism, I see Sarin’s work as pulling from… Read “Helena Sarin: Why Bigger Isn’t Always Better With GANs And AI Art” for the rest of Bailey’s foreword and Helena Sarin’s important paper “Neural Bricolage” in its entirety. 

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Artnome

Jason Bailey is an art nerd trying to trigger an art analytics revolution. Jason is mission driven to use technology and data to improve the world's art historical record and to bring attention to artists working at the intersection of art and technology.

Art

Tech

Curators' Choice

Generative Art Tools

Generative Art Tools

Sep 6, 2020 Events

Generative Art Tools

SuperRare
4 years ago

By Yura Miron

Yura Miron is a visionary artist exploring the inner and outer universes using the new media art tech, such as: VR, GAN, generative art and blockchain. Inspired by his visionary psychedelic experiences, lucid dreaming and by being constantly aware of his own presence. Working with such themes as: visionary mystical experiences, fusion of nature and technology, solarpunk, eco-speculation, science fiction, quantum and astrophysics, micro and molecular biology.

In this article I’d like to talk about some fascinating generative tools that are available to download and experiment by any artist. First I’d like to give you some of my art background.

All of my life I’ve been drawing and I’ve decided to dedicate my life to art around 9 years ago, when I was 20 y/o. For the first 4 years I’ve been only drawing all days long, generating 3-4 finished drawings every day. I’ve been learning arts very fast. I’ve been working on developing my unique style, playing with compositions, colors and technics. 6 years ago I’ve discovered the whole new fantastic world – new media art. I’ve started 3D sculpting, VJing and animating my drawings. I’ve been very productive and posted everyday new artworks on my social media blogs my artworks, and have gained lot of followers, for example on Tumblr there was 100K+ of followers. And still there was no way of me making money of my digital art.

In 2015 I’ve first tried painting in VR and my life as an artist was completely changed forever by it. Together with my friend we’ve created a mixed reality lab, where artists could explore VR and AR tech in their art practices. I’ve taught for than 1000 people how to create art/sculpture/animation/design in VR in 2016-18 years. In 2016 together with Serge Synthkey we’ve created our musical duo project called SYNXRON. We’ve been doing many live shows, mostly electronic dance music (techno/house/acid/modular/ambient/idm), did lives on opening of some cool art exhibitions, made collaborations with dancers, choreographers, media artists, laserjays and designers. Also I’ve been working with VJ Yarkus on many shows as a laserjay. Laser light is something of absolutely magnificent nature. The main point of all those collaborative live shows was the real time connection with an audience. When I’ve had all my set-up working properly, at any given moment I’ve been able to generate anything unexpected and influence its output all of the time. The main mission of our performances was to create an immersive audio-visual experiences for different people in different locations. And everybody who’s watching my visuals or listening to my music were also co-creating it with me, as it influences my outcome in real-time as well. So this is more like a controlled chaotic feedback-loop, than a predicted order.

In the late 2018 I’ve felt really burned out and decided to stop making music with Serge and teaching and laserjaing. Working on laser shows and teaching VR, while making an album, practicing for next live shows over and over again and having ongoing troubles in my personal relationship, I’ve decided to leave it all behind, being grateful for the experience, and moving further. I needed to get back to my core, to zero. I’ve felt that I need to focus on my Art again. I’ve started creating “Pure Abstractions” back then. Suddenly then I’ve discovered cryptoart. Blown away with it’s possibilities I’ve started searching for the main platforms where I could start tokenizing some of my best artworks. Luckily, I’ve been accepted as an artist on all of them. I remember one day I’ve seen ‘Latent Space of Landscape Paintings #1’ by @videodrome.

Latent Space of Landscape Paintings #1
Edition 1 of 1
Tracing the perimeter of a high dimensional sphere through the latent space of AI generated landscape paintings.

I was pretty much amazed by it! I’ve started learning about GANs and how they work. I’ve found Ganbreeder (now it’s called Artbreeder https://www.artbreeder.com/ ) and it was exactly what I’ve been looking for. I’ve been ganbreeding for hours, just like I’ve been drawing before. I’ve had a feeling that this is something really surreal and beautiful! I’ve generated thousands of artworks using this tool, and made created around 200 different animated loops with it (half of them are already tokenized to). I’ve been breeding static artworks, and crossbreed between them, saving frame-by-frame. Later I’ve learned automate this process it using some coding in Python (copy-paste from instructions), before the animation editor was finally built into Artbreeder. I remember how I’ve put up the very first GAN animation of mine. It was ‘Agfom Potent-Shot’:

Agfom Potent-Shot
Edition 1 of 1

It completely brew my mind, how close this artwork was to some of my visions generated by magic mushrooms and I’ve continued exploring this new unexplored (by myself) territory.

I love the way how I’m able to choose where the evolution of an artwork will go, by selecting the best artworks. Also I’ve been crossbreeding a lot between different pictures. It’s a wonderful tool for an artist. I think that an artist becomes a curator in this situation. I imagine a factory of artists, hundreds of artists working all the at once to paint art, and my role is to select the best ones. Only a few super wealthy artists can really hire hundreds of other artists in real world, but with Ai tools now any artist can do that virtually.

Now I’d like to talk about some other fascinating generative tools that I’ve been exploring lately.

First one is Physarum simulation by Sage Jenson. A true cosmic generation experience. God-like feeling J

Here’s how he describes it by himself: “This February I spent a bit of time simulating slime mold (Physarum polycephalum). I saw some incredible posts by Georgios Cherouvim with reference to a 2010 paper by Jeff Jones, “Characteristics of pattern formation and evolution in approximations of Physarum transport networks.” When I read the paper, I was excited to learn that the model combined continuum and agent-based simulation systems in a way that I hadn’t seen before. In this post I try to describe some of the concepts behind the system, and give an overview of how it functions.

There are two requirements of efficiency in foraging behavior: 1.) to search a maximal area and 2.) to optimize transport distance. Physarum polycephalum is a unicellular multinucleate organism that excels at these two competing tasks through the mechanisms of growth, movement, and area reduction. When the organism can choose to travel through two different paths to a destination, the emergent behavior allows it to effectively find shortest paths. This allows Physarum to navigate mazes, develop optimal road-like systems and solve other path-finding problems.

The model postulated by Jones employs both an agent-based layer (the data map) and a continuum-based layer (the trail map). The data map consists of many particles, while the trail map consists of a 2D grid of intensities (similar to a pixel-based image). The data and trail map in turn affect each other; the particles of the data map deposit material onto the trail map, while those same particles sense values from the trail map in order to determine aspects of their locomotion.

Each particle in the simulation has a heading angle, a location, and three sensors (front left, front, front right). The sensor readings effect the heading of the particle, causing it to rotate left or right (or stay facing the same direction). The trail map undergoes a diffusion and decay process every simulation step. A simple 3-by-3 mean filter is applied to simulate diffusion of the particle trail, and then a multiplicative decay factor is applied to simulate trail dissipation over time. The diagram below describes the six sub-steps of a simulation tick.

Many of the parameters of this simulation are configurable, including sensor distance, sensor size, sensor angle, step size, rotation angle, deposition amount, decay factor, deposit size, diffuse size, decay factor, etc. For a more detailed description check out the original paper.”

He implemented the model in C++ and GLSL using openFrameworks. All of the computation and rendering happen on the GPU, which stores both the particle information and the trail map. The simulation runs in real-time on a GTX 1070, with most of the examples comprised of between 5 and 10 million particles.

https://sagejenson.com/physarum

I did not receive any answer from Sage, asking if I could experiment with his amazing tool. So I’ve started searching for any other software where I can generate Physarum simulations and I’ve found one created by nicoptere on Github https://github.com/nicoptere/physarum

Here’s what I’ve generated with it:

Another software that I’ve been enjoin lately is Egregore. “Egregore – source” is an adaptation of the software used by chdh for the performance egregore in 2011-2014. It is based on five different audiovisual instruments made of chaotic and physical modeling algorithms that you can directly control. It is available as a software to download or as a usb stick. Download the software here: http://www.chdh.net/egregore_source.php

Here’s my today’s experiments with it:

Next tool I’d like to discuss is ‘Cosmic Sugar’ – a simple but elegant GPU driven simulation space. VR conrollers become attractors or repulsors which allow you to craft nebulae. A very beautiful VR tool: I’ve imagined that one day I’ll be able to generate millions of particles using my hands in VR, real-time, and here’s this tool – just like I wanted it to be. Highly recommended software.

Here’s me playing with it for the first time yesterday:

http://cosmicsugarvr.com/

 

Next tool is called Vsynth – A modular virtual video synthesizer and image processor package for Cycling’74 Max environment. Vsynth was created by Kevin Kripper, a new_media artist, indie developer and teacher based in Buenos Aires.

I’ve created 3 music videos for my musician friends Luna-9. Here’s one of them:

https://www.patreon.com/vsynth

Here’s a link on his Patreon, where you can download the software and many cool patches by subscribing to his pateron page for only 5$/mo

The next tool is perfect for VJing (my passion for the last 6 years – I’ve been VJing on many parties/festivals/raves) is Microdose VR – a trly fantastic software for live performances and music videos.

 

Microdose VR combines art, music and dance into a realtime generated creative virtual reality experience. Microdose VR is created by Vision Agency, a VR centric studio based on Colorado, USA, founded by Android Jones, Anson Phong, Scott Hedstrom and Evan Bluetech.

Microdose VR is currently in beta development and only in use by a very small circle of testers. The only way to try Microdose VR is to find us at an event that we’re at. If you have an HTC Vive or Oculus Rift with touch controllers and would like to obtain Microdose VR, you can get yourself on the list to beta test by sending a private message to this FB page, requesting to be in the beta test group. https://www.facebook.com/microdoseVR/ or you can do the same using Discord (that’s the way I’ve got my beta-tester key) https://discord.gg/t43TsSp

This is my upcoming artwork for the Cryptograph https://cryptograph.co All of my proceeds (70%) will be donated to the “Many Hopes”charity https://www.manyhopes.org Created using MicrodoseVR:

I’m going to tokenize many new artworks created with these amazing generative tools.

I hope you’ve enjoyed my article and learned something new and valuable. Thank you!

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SuperRare

SuperRare is a marketplace to collect and trade unique, single-edition digital artworks.

Art

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Curators' Choice

Cryptowave: Sculptures and Music by Studio Nouveau

Cryptowave: Sculptures and Music by Studio Nouveau

Sep 5, 2020 Artist Statements

Cryptowave: Sculptures and Music by Studio Nouveau

SuperRare
4 years ago

Project Studio Nouveau is a collaboration between Ture and Kaja Olson, who strive to create multimedia pieces that are greater than the sum of their parts.

As Ture has been a professional musician for much of his life, Studio Nouveau was partially born out of the havoc wreaked on the live music industry by the COVID-19 pandemic. “Once it wasn’t possible to perform music live, my creative energy naturally flowed to my deepest passions, which are the intersection of visual art, music, and blockchain.”

Kaja, who has academic training in fine art and art history, and now focuses on digital drawing and photo editing, offers a curatorial and technical eye, being very key to the process of melding the disparate elements being combined in each piece –  “I apply my knowledge of the foundational elements and principles of art to help refine Ture’s pieces during earlier parts of the creation process, and I assist in merging the pre-video visual components together into one cohesive final image.”

Studio Nouveau’s works take the form of audiovisual pairings, with a striking abstract style that incorporates digital sculptures, GAN-generated landscapes, music, and video effects. Presented in a video format, the duration is dictated by the music, which is usually structured to be between 1:00-1:30 minutes.

In constructing the audiovisual pairings, the idea is to create a cohesive yet abstract respite for the viewer to experience.

Mist
Edition 1 of 1
An audiovisual pairing that combines an image of a sculpture (“A.I. Sculpted Structures”), a GAN generated landscape, and music. These elements are displayed in a video format with additional visual effects.
https://superrare.com/artwork-v2/mist-11868

Ture digitally handcrafts the sculptures and music for each piece and places a high premium on creating a world of fine details for the listener to seek out, creating a fresh experience with each repeated watch and listen.

In terms of the musical style Ture employs in his work, it is very much a conglomerate of different genres and styles that have been internalized throughout his life. The resulting sound is meant to be a musical rhetoric that is accessible yet refined.

The blockchain-native nature of Studio Nouveau’s work, in addition to the electronic elements of Ture’s music, have led him to describe Studio Nouveau’s style as a new genre he is calling “cryptowave.”

Commenting on the state of the music industry today, “In the world of unfettered music streaming, music has an infinite supply, and therefore very little value that can benefit the creator. When art and music are native to a blockchain, an artist can share their work with the world, while maintaining an immutable digital link to the original creation of their work.”

During the early stages of Studio Nouveau’s development, Ture discovered the platform “Artbreeder,” which allows users to generate new images through different types of open-source GANs (Generative Adversarial Network). Ture was particularly inspired by the landscapes he was able to create using the platform, and this quickly became a staple of Studio Nouveau’s work.

Another of the early experiments that inspired the initial creation of Studio Nouveau was Ture’s creation of abstract sculptures in the digital modeling software Blender. It became a medium of expression that has snowballed into the work that you see today.

Flow
Edition 1 of 1
An audiovisual pairing that combines an image of a sculpture (“Digital Cast”), a GAN generated landscape, and music. These elements are displayed in a video format with additional visual effects.
https://superrare.com/artwork-v2/flow-12115

The sculptures that are used in each audiovisual pairing are displayed in Studio Nouveau’s recently opened art gallery and sculpture park in Decentraland, an ethereum-based virtual world.

In creating a sculpture park in Decentraland, Ture was particularly inspired by the famous sculpture park “Storm King,” north of New York City, which is a beloved place for Ture and Kaja.

In addition to his artistic pursuits, Ture has also been a crypto-enthusiast since mid-2017. “Ever since I dove deep into learning about crypto, Ethereum, and ERC-721 tokens, I knew that I had to find a way to tokenize my work. Decentraland became a part of the vision for how I would achieve this.”

Initially, Studio Nouveau presented Ture’s sculptures independently from the GAN landscapes and music. However, after discussing Studio Nouveau’s work with artist Bryan Brinkman, Bryan suggested that it might be interesting to combine the sculptures, GAN landscapes, and music into one cohesive composition. Ture loved the idea, and immediately seized on it.

The resulting pieces are what helped Studio Nouveau to become accepted as a SuperRare artist, and is consequently the work they have begun tokenizing.

Studio Nouveau can be found on SuperRare at: superrare.com/studionouveau

To learn more about the project, visit Studio Nouveau’s website: www.studionouveaudcl.com

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