What should i do next?
Start date: 08.03.2021 00:08:35 | End date: 09.30.2021 23:09:00 | Created by: mieserfettsack
You can vote on what my next project will be. I will not work on this myself. I will buy myself a freelancer for it. Buy a new layout for theaterkompass.de. Estimated effort: 7 days Implement facet search for theaterkompass.de. Estimated effort:5 days Include new feature for all theaters in German-speaking countries. Database already exists. Estimated effort: 5 days Make all my TYPO3 extensions TYPO3 11 compatible. Estimated effort. Estimated effort: 3 days Create a staging system for my TYPO3 projects: Estimated effort. Estimated effort: 5 days Just publish something new on gitlab. Estimated effort: 1-2 days
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We are excited to announce the latest features of our DDEV Deployment Automation! This comprehensive suite of automation scripts simplifies managing DDEV environments across local, staging, and live setups. Our solution now offers a cost-effective alternative to complex cloud Kubernetes setups, ideal for small to medium-sized projects. https://gitlab.com/mdys/ddev-deployment-automation New features include: - Comprehensive Automation: Fully automated deployment and management of DDEV environments. Utilizes DBaaS and a separate instance for file storage, mountable via SSHFS. - Individual Review Environments: Each merge request gets its own environment with a unique URL and SSL. - Secure File Transfer: Automatic downloading and management of secure files. - HTTP Authentication: Easy setup of HTTP authentication for staging environments. - Read-Only Live Data: Live data can be mounted as read-only volumes in staging and local environments.
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