In May of 2023, I embarked on an experimental journey to fuse handmade digital paint into my existing body of work. While the endeavor was largely successful, I encountered some limitations, particularly with the square canvas size that I initially choose. This constraint affected the scope of artistic expression; long or thick paint strokes would dominate the entire canvas and there will also be no space for lines. Additionally, the raw landscape and flowers I created in midjourney, initially struggled to harmonize with the manual paint strokes and color palettes in photoshop. Despite these challenges, this experiment has been a pivotal exploration for my practice. Using a long vertical canvas this time, the raw landscape from using midjourney brings a precise, algorithmic beauty, contrasting yet complementing the organic aspect of nature and fluid strokes of human-applied paint. The colors, paint strokes, lines, and landscapes, though initially discordant, have also started to find a balance, mirroring the slow but beautiful ways in which nature and humans co-exist today. With this, "Unexpected" became a testament to the possibilities that arise when machine, humans, and the natural world intersect on a single canvas. All collectors have until November 30, 2023, to claim a physical signed print. Each edition will be only printed only once. To claim the 22x39cm print on Hahnemühle Photo Rag 308gsm, you must provide proof of ownership of the NFT at the time of claiming.

Wren

Unexpected #17

From

Unexpected

Description

All collectors have until November 30, 2023 to claim a physical signed print. Each edition will be only printed only once. To claim the 22x39cm print on Hahnemühle Photo Rag 308gsm, you must provide proof of ownership of the NFT at the time of claiming.

Artist
Wren
Blockchain
Ethereum
Token standard
ERC-721
Contract address
0xae...0f27
Token
14
Ecosystem
Desert
Fabric
Cream
Lines
40%
Paint
10%
Palette
Robinia pseudoacacia
Season
Autumn
Sky Condition
Clear Sky
Time of Day
Midday
Activity
ArtworkPriceFromToTime