The creator and lead dev of the popular NFT exchange Hic Et Nunc on the Tezos blockchain decided to shut down the project. He pulled the plug on the whole website and the official Twitter account.
Yet, the damage is not fatal π
How come?
β NFTs are fine - they are stored on the blockchain
β NFT metadata is fine - stored on IPFS
β Exchange backend code is fine - it is in an immutable smart contract
β The website is back online - it is open-source, so a clone was deployed by the community fast
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Of course, this is a dramatic event and the quick recovery was only possible because of the immense effort of the community. But it is possible and it took basically 1 day.
Imagine the damage that the creator and lead dev could do if they want to destroy a Web 2.0 company!
How I made $3000 in 3 weeks selling AI-generated art? π°
Last week I showed you how you can use VQGAN+CLIP to generate interesting images based on text prompts.
Now, I'll tell you how I sold some of these as NFTs for more than $3000 in less than 3 weeks.
Let's go π
Background
I've been interested in NFTs for 2 months now and one collection I find interesting is @cryptoadzNFT. What's special about it is that the creator @supergremplin published all of the art in the public domain. This spurred the creation of many derivative projects.
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The Idea π‘
My idea was to use VQGAN+CLIP to create interesting versions of the CrypToadz. So, I started experimenting with my own toad #6741.
I took the original NFT image as a start and experimented a lot with different text prompts. The results were very promising!
In their latest paper, they introduce the so-called verifiers. The generative model generates 100 solutions, but the verifiers select the one that has the highest chance of being factually correct.
You've probably seen these strangely beautiful AI-generated images on Twitter. Have you wondered how they are created?
In this thread, I'll tell you about a method for generating art with ML known as VQGAN+CLIP.
Let's jump in π
Short History π
In January @OpenAI publicly released CLIP, which is a model that allows matching text to images.
Just days after that, some people like @advadnoun, @RiversHaveWings, and @quasimondo started experimenting using CLIP to guide the output of a GAN using text.
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OpenAI published an image generation model together with CLIP, called DALL-E, but without the full code and the pre-trained models.
The results from guiding StyleGAN2 or BigGAN with CLIP aren't as accurate as DALL-E, but they are weirdly artistic.
There is a problem with how value is distributed in online communities today. It seems we take the status quo for granted and don't discuss it much.
The people that create most of the value, get none of the money! Only badges...
Thread π
Online communities
I'm talking about platforms like Twitter, Reddit, Stack Overflow etc. They're wonderful places, where you can discuss interesting topics, get help with a problem, or read the latest news.
However, the people that make them truly valuable receive nothing π
It usually looks like this:
βͺοΈ Company creates a web 2.0 platform
βͺοΈ Users create content and increase the value
βͺοΈ Company aggregates the demand
βͺοΈ Company monetizes with ads and subscriptions
βͺοΈ Company gets lots of money
βͺοΈ Creators get badges, karma and virtual gold