How Generative Artist Tyler Hobbs Became an NFT Multi-Millionaire


The production of Fidenza by Tyler Hobbes did not harm the paintbrush. Photoshop was never opened in his Holly neighborhood studio. Hobbes, who turned from a computer scientist to a generative artist, has now created a viral art collection entirely from raw code lines. “Take your stereotyped hacker scene in a movie where they’re typing words on a black console,” he says. “It’s basically what I see and work on.”

Since hitting the blockchain (a huge decentralized digital ledger where transactions are stored) in June 2021, Fidenza has caused a storm among NFTs (non-alternative tokens). Since then, it has turned Hobbs into a cryptocurrency billionaire with over $ 277 million in secondary sales.

Here, Hobbs shares the details of the code underneath his colorful and abstract work of art.

Fidenza # 953 It has the most common color palette “Luxe” in the collection. Half of all Fidenzas use this color scheme, but with 16 different hues built in, “there’s still plenty of room for unique results,” Hobbs says.

Another element of the code creates a soft texture with a particular output. Fidenza # 774.. According to Hobbes, this effect is achieved using thousands of small parallel lines. “Other standard Fidenza simply fills each shape evenly with a bolder, graphic-looking color.”

Hobbs ran the Fidenza algorithm 999 times, each using a random number (buyer’s randomized transaction number, or hash) to produce 999 different outputs. According to Hobbes, randomness is an important element of his work, including his latest project. Incomplete control.. “Sometimes even better than intentionally designed ones will happen.”

In his point, some of the greatest achievements of the Fidenza collection are the result of an accident. Fidenza # 313The flower, which was resold last summer for $ 3.3 million, was nicknamed “Tulip” because it unintentionally resembled a flower. On the other hand, “God mode” or Fidenza # 938 is an extreme outlier. As a result of a bug accidentally breaking into the final code, Hobbs states: “It combines a number of unlikely features. In fact, I have never observed those combinations while developing the algorithm.”


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