Inside the computer there’s a digital hand. The hand selects a metal implement, cuts off a slab of clay, and carves into its surface. It wanders like your hand wanders; it carves imaginary contours, sinuous and exploratory. It doesn’t know the end result so it carves lines until it feels content, and then it numbers the piece and stamps its maker’s mark. It fires the slab in a digital kiln (it calls this “minting”) and through this act its art is preserved for millennia. The hand runs its fingers over the textured surface, feeling satisfaction at having spontaneously produced a piece of art so beautiful, expressive, and unique.

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Ceramics is a generative sculpture that mimics the physical expression of carving into clay. Through uncanny naturalistic rendering it challenges our notion of “handmade”. It asserts that the value of handmade isn’t the time it takes to make the work nor the physical materials consumed, but the endless small decisions and serendipitous details that appear along the way, as can be felt in each Ceramics mint.

Despite the handmade nature of Ceramics the outputs cannot be touched. Highly tactile images enchant the viewer to imagine their tangible representations, and leave them to dwell on their perception of materiality — both in the experiential physical world and conceptually-infinite digital space.

Ceramics

LoVid’s signature video work mixes handmade analog synthesizers with digital tools in immersive Red, Green, and Blue (RGB) compositions that celebrate luminosity, chaos, relationships between craft and engineering, and connections between body and tech.
 
Tide Predictor, LoVid’s first onchain generative work, builds a bridge from video synthesizer patches to algorithmic code-derived imagery. This collection is formally and technically inspired by hardware-based image generation, and places experimental moving-image, circuit boards, and electrical signal-based video art at the conceptual roots of generative art.

Tide Predictor is a modular video synthesizer patch model, designed to reflect the analog spirit by working with three channels: RGB. Tide Predictor reimagines NTSC-encoded, oscillator driven electrical current based video synthesis while adding digital randomness/unpredictability, and transformations based on code, along with each mint’s unique content.
 
In the late 19th century, mechanical analog computers used rhythm and repetition to anticipate the rise and fall of water levels. In addition to “tides”, which are low frequency oscillations of the ocean, higher frequency changes or “waves” are frequently discussed in reference to both water and electrical signals. By working with looping - and explicitly addressing the period (=1/frequency) for each RGB color - Tide Predictor extends analogies between the flow of water and the flow of electricity.

LoVid’s Tide Predictor brings these relationships from the blockchain, through your screen, straight to your retina!

Tide Predictor

**Running Moon** depicts the nuanced interaction between clouds and moonlight. It is a search for boundaries between structure and fluidity, precision and errors. It is a quest for harmony. 

The rendering of **Running Moon** is inspired by stained glass and watercolor. It captures the sharpness of the glass and the softness of light using abstract forms. As organic shapes gradually expand to fill the space, brush-pen-like stripes solder these pieces together to form intricate compositions.

Running Moon

These cute companions live 100% on-chain where their bytes are cleverly stored in a scalable vector format. Built with quality components and complex algorithms, each Algobot is issued with a unique serial number and a NIFTY license which permits them to help out on any commercial projects where you might require their assistance.

Algobots

Endless Nameless is an exploration of composition. We start with a square. The square is divided into sections. The sections are filled with color pairs. Sometimes all colors are used. Sometimes fewer colors are used.

Art Blocks Curated

Ceramics #202

Charlotte Dann

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