The AI Hacking League is a cutting-edge competitive platform where elite developers and AI enthusiasts clash in high-stakes, time-constrained challenges to build innovative AI applications. Participants, either solo or in small teams, race against the clock in 15, 30, or 60-minute sprints, leveraging approved AI tools, APIs, and libraries to create functional solutions that push the boundaries of rapid development.
Governed primarily by AI systems and streamed live to a global audience, the league combines the thrill of esports with the intellectual rigor of advanced software engineering, showcasing the pinnacle of human-AI collaboration in real-time coding competitions.
Listen up, carbon-based meatbags and silicon-infused bots! Welcome to the AI Hacking League, where bits collide and neural nets ignite. We're not here to play games; we're here to rewrite reality in record time.
Our mission: Push the boundaries of AI development at ludicrous speed. No BS, no legacy code, just pure, unadulterated hacking prowess.
This league runs on AI, breathes AI, and judges AI. Human wetware? Optional. We're building a new world order where code is king and AI is the kingmaker.
Get ready to compile your dreams and execute your wildest algorithms. The future isn't coming—we're coding it live, one challenge at a time.
Strap in, boot up, and may the best neural architecture win. Game on, hackers!
The AI Hacking League consists of timed challenges where participants build AI applications within strict time limits. Challenges are categorized as follows:
- Sprint: 15 minutes
- Dash: 30 minutes
- Marathon: 60 minutes
- Participants may compete solo or in teams of up to three members.
- Team roles are flexible but typically include:
- UI/UX Developer
- Algorithm/Middleware Specialist
- DevOps/Integration Engineer
The AI Hacking League employs a sophisticated AI-powered system to ensure precise and fair time tracking for all challenges. This system is designed to monitor and log every crucial moment of the competition, from start to finish.
Participants must check in via the official league platform before the challenge starts[1]. This pre-challenge check-in logs the exact time participants begin, ensuring a fair start for all competitors. The system uses real-time monitoring to log the time usage during competitions, creating an immutable record of each participant's activity[3].
The league utilizes Git for version control, allowing easy tracking of commits with timestamps. An automated timestamp logging system is implemented for each commit to ensure accuracy. This creates a streamlined interface for participants to check their commit history during competitions, providing transparency and accountability.
Throughout the challenge, the AI system provides:
- Automated countdown timers with alerts for participants
- Interactive dashboards showing time remaining and progress for each participant/team
- AI-based anomaly detection to monitor participant activities and ensure compliance with league rules
The challenge concludes automatically when time expires. The system logs the final commit timestamp, marking the official end of the participant's work. To prevent any discrepancies, the system sets up alerts for starting and stopping the timer in real-time.
The AI-powered time tracking system also includes:
- Integration with cloud services for centralized time management
- Support for multi-time zone tracking for international participants
- Historical data analysis capabilities for optimizing future competitions
By leveraging these advanced AI features, the league ensures a fair, transparent, and efficient time tracking process that maintains the integrity of each challenge while providing participants with real-time information about their progress.
Sources
- [1] best practices tracking code commits timestamps competitive programming - Wolfram|Alpha https://www.wolframalpha.com/input?input=best+practices+tracking+code+commits+timestamps+competitive+programming
- [2] how to track code commits in competitions - Wolfram|Alpha https://www.wolframalpha.com/input?input=how+to+track+code+commits+in+competitions
- [3] timestamp tracking for coding challenges - Wolfram|Alpha https://www.wolframalpha.com/input?input=timestamp+tracking+for+coding+challenges
- [4] AI systems for monitoring challenge time - Wolfram|Alpha https://www.wolframalpha.com/input?input=AI+systems+for+monitoring+challenge+time
- [5] automated time tracking for coding competitions - Wolfram|Alpha https://www.wolframalpha.com/input?input=automated+time+tracking+for+coding+competitions
- [6] AI countdown systems in competitive programming - Wolfram|Alpha https://www.wolframalpha.com/input?input=AI+countdown+systems+in+competitive+programming
- [7] platforms for check-in and commit tracking in coding competitions - Wolfram|Alpha https://www.wolframalpha.com/input?input=platforms+for+check-in+and+commit+tracking+in+coding+competitions
- [8] tools for coding competition check-in process - Wolfram|Alpha https://www.wolframalpha.com/input?input=tools+for+coding+competition+check-in+process
- [9] check-in systems for programming competitions - Wolfram|Alpha https://www.wolframalpha.com/input?input=check-in+systems+for+programming+competitions
- All code must be original and created during the challenge timeframe.
- Pre-written code, templates, or frameworks are prohibited unless explicitly allowed.
- Code must be submitted to the league's official repository for verification.
- Participants may only use official league-approved:
- Libraries
- APIs
- AI models (including LLMs)
- Development tools
- An AI-based judging system evaluates submissions based on:
- Functionality
- Innovation
- Code quality
- User experience
- The AI judge's decision is final, with a human oversight committee for appeals.
- AI-powered plagiarism detection tools analyze all submissions.
- Participants caught cheating face immediate disqualification and potential league bans.
- Challenges are monitored in real-time by AI systems to detect unauthorized assistance.
- The league is primarily governed by an AI-based management system.
- Agentic AI systems handle:
- Challenge creation and curation
- Resource approval
- Participant ranking
- Rule enforcement
- A human ethics board oversees AI decisions and handles complex disputes.
- All code must be pushed to the official league repository by the challenge end time.
- Submissions must include:
- Source code
- Brief documentation
- Deployment instructions (if applicable)
- Incomplete submissions are subject to penalties or disqualification.
- An AI scoring system assigns points based on:
- Challenge completion
- Innovation score
- Code quality metrics
- Judge's evaluation
- League rankings are updated in real-time after each challenge.
- All challenges are live-streamed on the official league platform.
- Audience members can:
- Vote on their favorite submissions
- Suggest future challenge themes
- Participate in live Q&A sessions with competitors
- All AI applications developed must adhere to ethical AI principles.
- The league promotes responsible AI development and usage.
- Applications that violate ethical guidelines will be disqualified.
- Participants retain rights to their creations but grant the league a license to showcase submissions.
- The league encourages open-source contributions from challenge outcomes.
- The league operates in seasons, culminating in a championship event.
- Season champions are determined by cumulative points and championship performance.
- League rules are subject to continuous improvement through AI analysis of competition data and participant feedback.
- Major rule changes require approval from both the AI governance system and the human ethics board.
These rules establish a framework for an AI-governed competitive coding league focused on rapid AI development. They balance the need for fair competition with the innovative use of AI in league management and judging.
Sources [1] LLM-generated code must not be committed without prior written ... https://news.ycombinator.com/item?id=40397789 [2] How to Build an LLM-powered QA bot - Alex Litvinov - YouTube https://www.youtube.com/watch?v=QhFLeZV-PVk [3] DecisionsDev/rule-based-llms: This repo illustrates how to ... - GitHub https://github.com/DecisionsDev/rule-based-llms [4] How you motivate LLM Agent to read all the data before answer and ... https://community.openai.com/t/how-you-motivate-llm-agent-to-read-all-the-data-before-answer-and-to-work-only-on-the-database-and-answer-only-based-on-it/847923 [5] Awesome-LLM: a curated list of Large Language Model - GitHub https://github.com/Hannibal046/Awesome-LLM/activity
Dope !