Last price
24h/30d change
24h/30d volume
24h/30d volume
Buy Depth
Buy Order
Sell Order
Buy Orders
Total:
MINTME
Sell Orders
Total:
MDYS
Trade History

MDYS is my private token. It was created to support me and mostly my open source work. The money that I will create with this token should ensure that I no longer do my regular work and that I only dedicate myself to OpenSource or Minteme projects. The more I am supported, the more projects can benefit from me. What I will do in detail with the money I will receive by selling the tokens * Cover the running costs of GitLab, cloud services and scaleway * More time for my pro bono projects like https://www.theaterkompass.de/ * Add more features to coinimp miner for TYPO3 https://gitlab.com/mieserfettsack/coinimptypo3 * Buy back MDYS from market Services you might get through a direct donation Migration of TYPO3 projects to fully CI / CD at GitLab Migration of composer based PHP projects to fully CI / CD at GitLab It doesn't cost anything to ask. You could reach me in the Discord: mieserfettsack#5804 All of my projects are on GitLab. Here you can find an overview: https://gitlab.com/mieserfettsack kthxbye!

Created on:
18 Sep 2020
Holders:
333
Already released:
10 000 000.0000
Not yet released:
0.0000
Active orders:
3 977.0000
Created on:
18 Sep 2020
Active orders:
3 977.0000
Release period:
0 year(s)
Hourly installment:
0.0000
Already released:
10 000 000.0000
Holders:
333
Wallet on exchange:
3 019 274.8805
Withdrawn:
4 900 000.0000
Sold on the market:
2 090 673.6195
Not yet released:
0.0000
Direct buy volume:
0
Latest News
21:05:17 28 May, 2024

A groundbreaking project has been launched to automate the analysis of Unreal Tournament 99 (UT99) demo files using OpenAI's GPT-4. The initiative aims to develop a Python script capable of accurately determining the playtime of UT99 demos by deciphering their binary structure and extracting the necessary data. The project's methodology involves generating script suggestions through OpenAI's API and refining these scripts iteratively based on their performance. This innovative approach leverages AI to tackle the complex task of gaming analytics, significantly reducing the manual effort involved in the process. By systematically refining each attempt, the project seeks to achieve precise and efficient solutions. https://gitlab.com/mdys/openai-find-ut99-demo-structure