Hi everyone, in this article, I would like to describe our experience of creating NFTs using artificial intelligence. In the beginning, our idea was to use AI DALL-E to generate NFTs from our quotes, but then we slightly changed the concept. Now the benefits of using AI are only available for holders of a certain amount of NFTs, but more on that later.
Table of content:
1. Idea and process creation
The idea originates in our love for literature and modern technology. We tried to find a way to combine the two, to give people an opportunity to see with their own eyes the result of such a combination. Moreover, one of our goals was to empower users to become owners of something beautiful and, possibly, even to raise some money. Another reason we started creating NFTs is that usually all of them are very similar. Our goal was to generate ideas, concepts, not mere images.
We chose 7 classic authors and selected 700 quotes from their books. From each quote, you can create 10 unique NFTs. In addition, we offer 30 premium NFTs that you can find on the opensea (soon). Moreover, you will receive a paper book for each purchased premium NFT with the same NFT on the cover for free.
How it works
The process is based on an algorithm that generates an NFT from a lot of different small pieces of images that we prepared before for each quote. The minting process takes place right on the site after selecting a quote and is invisible to the user.
Customer’s side (What customer sees)
Сustomer only has to choose the quote that they like from 3 options. When an NFT image has been generated, it is stored on our website and the user has full access to it at any time.
? AI generated NFT-stories
One more thing that I’ve mentioned before is that we prepared a great deal for those clients who bought all our authors. When you have 7 NFTs (one from each author) you can get 1 unique NFT story of your choosing absolutely for free. AI Da Vinci helps us make stunning stories. You can see an example of such a story below:
Story generated from quote
Every product creation should start with research to understand the market and the target audience. What an average NFT buyer is like? Having asked ourselves this question, we began our research and came to such characteristics:
We have never done such products before so we reviewed a lot of NFT resources to understand the standard and tried to find direct competitors. Based on our personas we made rough wireframes to transfer all the knowledge that we have collected on paper. So we started creating a mood board to find the correct style for our audience to display our idea. First drafts of UX-writing were here as well to understand exactly how we want to communicate with our customers, to define the tone of voice. An interesting observation is that all NFT sites on resources for designers look almost the same, while real projects are very different from each other — from very simple 1 screen pages to very huge with a lot of animation masterpieces.
We want to move iteratively, step by step, to make sure we reach the end and we want our NFT buyers to know what our product development plan is. So here is the list of ideas and features that we created during brainstorming sessions. We have arranged it on the prioritization matrix to illustrate the implementation order.
This is the part of our research that I can share with you so that you can understand our way of thinking. This is the first iteration of our product, there is still a lot to be done, but a start has been made and you can see its results now.
We plan to launch our platform on September 1st, until then you can fill the gleam to get a chance to be whitelisted.
After the release we will be checking the metrics and trying to make our product better and better. We will keep you updated with new articles when there is something to talk about. We offer full-cycle blockchain development services, so if you are interested, you can go to our website and get acquainted with the services.
Thank you for your time, I hope you found something useful in this article.
Originally published at Medium on August 17, 2022 by Victor Zhitomirskiy.