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 #384

m4nu

“Computer Science (Death of)”, is composed of 100 unique generative artworks. The collection showcases the autonomous creative abilities of AI, free from human creative influence, culminating in a series of generative art pieces coded in p5js. The art was born from an elaborate iterative process, where AI was tasked to conceive, code, debug, and refine its own artistic concepts, constrained only by its maximum single response output.Imperfections in the artworks are intentionally preserved, symbolizing the raw and unrefined creativity of these early AI models. This collection serves as a historical snapshot capturing the frontier of AI's creative coding potential in 2023.

Computer Science #073

Study number 4 in Constructivist generative art.

Constructor #04

Study number 3 in Constructivist generative art.

Constructor #03

Study number 5 in Constructivist generative art.

Constructor #05

Study number 2 in Constructivist generative art.

Constructor #02

Study number 1 in Constructivist generative art.

Constructor #01

This artwork has been broadcasted on the German SAT.1 teletext starting from 11 JAN 22. The NFT contains the artwork and the associated pages in the native World System Teletext Level 1 broadcast format as well as their rendered 400x276 GIF versions, all created with the original TIUS teletext software. The artwork's teletext file has additionally been minted fully on-chain on Arweave to preserve teletext forever.

Arewave upload:

https://app.ardrive.io/#/file/5f6e9816-b5d4-480d-8d46-fdfd1a480902/view

Page 497 Quasimondo - Time is what we die of

Elman Mansimov, Emilio Parisotto, Jimmy Lei Ba & Ruslan Salakhutdinov
Department of Computer Science
University of Toronto
Toronto, Ontario, Canada

m4nu (m4nu_eth)

m4nu (m4nu_eth)

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