Sound Sculpture Uses Daisy Seed To Generate Audio

Here at Hackaday, we love a good art piece, whether that involves light or sound. Combining both is a sure-fire way to get our attention, and [Eirik Brandal] did just that with his Void Extrusion piece.

The project is built around the Daisy Seed from Electrosmith. It’s an embedded platform designed for musical purposes, which made it perfect for [Eirik]’s project. Based on an STM32 chip, it’s very capable when it comes to DSP tasks. In this role, it’s charged with algorithmic music composition, providing the captivating soundtrack that emanates from the sculpture.

The sculpture itself looks almost like a fancy mid-century home from the Hollywood Hills, but it’s fundamentally a little more abstract than that. [Eirik] built it as an opportunity to experiment with using 3D printed forms in his work. To that end, it features a beautiful diffused LED wall and a speaker enclosure as an integral part of the build. The LEDs are run from an Arduino Nano Every.

[Eirik’s] work shows us that “generative” music can be intoxicating and compelling with a real sense of feeling and mood. The sculpture is a visually-capable pairing that works with the soundscape. It recalls us of some other great artworks we’ve featured from [Eirik] before, too.

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Dittytoy recreation of Jean-Michel Jarre's Oxygene Part IV

Generative Music Created In Minimalistic Javascript Code

Dittytoy user [srtuss] has recreated one of the most influential works of electronic music in an elegant nineteen kilobytes of Javascript code. The recreation of Jean-Michel Jarre’s Oxygene Part IV on the Dittytoy platform, currently in beta, plays live right in your browser. Dittytoy empowers users to create generative music online using a simple Javascript API. Syntax of the API is loosely based on that of Sonic Pi, a code-based music creation and performance tool.

“Oxygene (Part IV)” was recorded by Jean-Michel Jarre in 1976. It was Jarre’s most successful single, charted on the top ten in several countries, and was more recently featured in the Grand Theft Auto IV video game. In the 1990s, famed electronic music innovator Brian Eno used the term “generative music” to describe music generated by an electronic system comprising ever-changing elements that may be algorithmic or random.

Recreation of Jarre’s work required modeling the Korg Minipops 7 drum machine, one of the instruments presented in our slew of open-source synthesizers.

A persons handing holding a pile of generative, laser cut snowflake ornaments

Laser-Cutting A Flurry Of Generative Snowflakes

It’s the holiday season, and what better way to celebrate than to carve out some generative snowflakes on your laser cutter? [Bleeptrack] has developed a web-based tool that creates generative snowflake ornaments which can be exported to SVG files ready-made for laser or vinyl cutting.

True to their namesake, each generated snowflake ornament is (very likely to be) unique, with multiple layers created that can be stacked on top of each other. [Bleeptrack] has showcased a few realizations, using semitransparent paper sandwiched between two top layer cutouts, made out of wood or cardboard.

The snowflakes are a great balance of minimal design while still being beautiful and rich in detail. They can be easily produced on any laser cutter or vinyl cutter that you might have handy. Source code is available on GitHub for those wanting to dive into the details of the web tool. Cutting one of your own would make a perfect addition to a Neodriver ornament or a tiny DOOM playing ornament. Video after the break!

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Can You Remembrandt Where This Is From?

A group of researchers have built an algorithm for finding hidden connections in artwork.

The team, comprised of computer scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Microsoft, used paintings from the Metropolitan Museum of Art and Amsterdam’s Rijksmuseum to demonstrate these hidden connections, which link artwork that shares similar styles, such as Francisco de Zurbarán’s The Martyrdom of Saint Serapion (above left) and Jan Asselijn’s The Threatened Swan (above right). They were initially inspired by the “Rembrandt and Velazquez” exhibition in the Rijksmuseum, which demonstrated similarities between the artists’ work despite the former hailing from the Protestant Netherlands and the latter from Catholic Spain.

The algorithm, dubbed “MosAIc”, differs from probabilistic generative adversarial network (GAN)-based projects that generate artwork since it focuses on image retrieval instead. Rather than focusing solely on obvious factors such as color and style, the algorithm also tries to uncover meaning and theme. It does this by constructing a data structure called a conditional k-nearest neighbor (KNN) tree, which provides a tree-like structure where branches off a central image indicate similarity to the image. In order to query the data structure, these branches are followed until the closest match to an image in a dataset is found. In further iterations, it prunes unpromising branches in order to improve its time for new queries.

Some results from running the algorithm against museum collections were finding similarities between the Dutch Double Face Banyan and a Chinese ceramic figurine, traced to the flow of porcelain and iconography from the Chinese to the Dutch in the 16th to 20th centuries.

A surprising result of this study was discovering that the approach could also be applied to find problems with deep nerual networks, which are used for creating deepfakes. While GANs can often have blind spots in their models, struggling to recreate certain classes of photos, MosAIc was able to overcome these shortcomings and accurately reproduce realistic images.

While the team admits that their implementation isn’t the most optimized version of KNN, their main objective was to present a broad conditioning scheme that is simple but effective for applications. Their hope is to inspire related researchers to consider multi-disciplinary applications for algorithms.

Whistle To Make The Art Flow

A new project from [James] targets the iPhone with this wild generative art in an Augmented Reality environment (free) app for 3GS and 4 running running iOS 4+. Powered by the String augmented reality library, and written in C + OpenGL the combo present a power AR platform offering over 100,000 polygons on screen with no noticeable dip in frame rate.

The artistic part is influenced by noise the app is picking up through the microphone. Speaking, whistling or blowing at the device creates 3D generative art, which you are then free to explore in 3 dimensions. It would be interesting to see what it comes up with in a naturally noisy environment. Features also include variety of 3D shapes, color palettes, and settings that can be mixed to create “endless” combinations along with a good to have save snapshot feature.

Join us after the break for a quick video, and be sure to check out some of [James] other work, like  the Augmented reality business card

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Art From Code: Generative Graphics

[Keith Peters]’ blog Art From Code is devoted to his beautiful graphics from computer source code, also known as generative art. Although [Peters] is reluctant to reveal his source code, algorithmic graphics can be created with the help of tools like ActionScript, Flash, and Flex. There are some great tutorials that can start you on the path to making your own evocative art.

[via Neatorama]