@LamboLanders

About the Artist / Project

Genesis Collection: Lambo Landers

@LamboLanders

NFT

Lambo Landers is the first collection I had ever created when I kicked off my NFT journey. Hot off the tail of building spaceships in games and doing a few modules in programming, I was fascinated by the possibilities of generative art and wanted to try my hand at it. This melded well with my enthusiasm for blockchain technology.

Thus, Lambo Landers was born. It also marked some of my first entries in the Dev Log. I had zero intentions of making any kind of profit from this as it was a learning exercise for me.

The project was a success. I had successfully created a generative art collection complete with its own metadata, smart contract and dapp to boot.

I made a few sales in the space from a few people that liked them at the time. But nothing notable.

They are currently used as an Airdrop reward as they all have been minted from the contract and the dApp has been decommissioned.

Sales are available from on OpenSea secondary through the Lambo Landers/Holder accounts or via Airdrops only.

When Collection 2 (CRASH) gained some popularity, a lot of questions where raised about the original LamboLanders collection. To my surprise, Collection 1 had a high amount of interest during CRASH however at the time it was created I never bother marketing the project to my nearly 200 twitter followers.

Comments and requests had come through to reboot Collection 1 however if I were to do this I needed to give my spaceships the launch they deserved. Following some research into voxel generative pieces and 3d model viewers the LamboLanders: Reloaded earnt itself a second wind.

RELOADED sees the original collection, traits and rarities reviewed and rebooted in a Sandbox-Ready metaverse style format. The models are genuine 3D Objects that can be rotated by swiping on your mobile device.

LamboLanders: Crash

@LamboLanders

Crash is a collection of 9000 unique cyber dystopian avatars which pilot the Lambo Landers.

The project aims to bring accessible and high quality NFTs to the blockchain. Each avatar in the collection has been put together using popular 3d programs to create a mixture of traits and characteristics, which are carefully inked and airbrushed in photoshop.

Once the artwork on the traits are completed; they are saved as individual layers in a folder directory and pressed together with a popular art engine – however, this is where Crash has introduced something new –

Crash NFTs are compiled without a background layer.

Instead, I have created additional code to randomly apply generative lighting as traits over each of the layers (also known as blend modes) – a technique that is not often found in 2d generative projects. The background traits consists of 3 layers, a foreground light, a background light and background wallpaper – this is combined with the generative art to make a phenomenal 2D avatar.

John Doe
CEO, Acme, Inc.

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John Doe
CEO, Acme, Inc.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

John Doe
CEO, Acme, Inc.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

John Doe
CEO, Acme, Inc.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

John Doe
CEO, Acme, Inc.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.

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