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ahl.md

Ai Hacking League

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.

AI Hacking League Constitution

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!

AI Hacking League Official Rules

1. Competition Format

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

2. Team Composition

  • 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

Time Tracking

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.

Initial Check-in

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].

Commit Tracking

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.

Challenge Progression

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

Challenge Conclusion

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.

Additional Features

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

4. Code Qualifiers

  • 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.

5. Approved Resources

  • Participants may only use official league-approved:
    • Libraries
    • APIs
    • AI models (including LLMs)
    • Development tools

6. AI Judging System

  • 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.

7. Anti-Cheating Measures

  • 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.

8. League Governance

  • 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.

9. Submission Requirements

  • 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.

10. Scoring and Ranking

  • 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.

11. Streaming and Audience Participation

  • 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

12. Ethical Considerations

  • 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.

13. Intellectual Property

  • Participants retain rights to their creations but grant the league a license to showcase submissions.
  • The league encourages open-source contributions from challenge outcomes.

14. League Seasons and Championships

  • The league operates in seasons, culminating in a championship event.
  • Season champions are determined by cumulative points and championship performance.

15. Rule Amendments

  • 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

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ai-powered-features.md

AI-Powered Features

The AI Hacking League leverages cutting-edge artificial intelligence to enhance various aspects of the competition. This document outlines the key AI-powered features that make our platform unique and innovative.

AI Judging System

Our AI Judging System is designed to evaluate code submissions quickly and objectively based on multiple criteria:

Evaluation Criteria

  1. Functionality (40%): How well does the solution solve the given problem?
  2. Innovation (30%): Does the solution present novel approaches or creative use of AI technologies?
  3. Efficiency (20%): How optimized and performant is the code?
  4. Code Quality (10%): Is the code well-structured, readable, and following best practices?

Technical Implementation

  • API Integration: We use OpenAI's GPT-4 model through their API to analyze code submissions.
  • Custom Prompts: We've developed specialized prompts that instruct the AI to focus on specific aspects of code evaluation.
  • Scoring Algorithm: A weighted scoring system calculates the final score based on the AI's evaluation of each criterion.

Feedback Generation

The AI generates detailed feedback for each submission, including:

  • Strengths and weaknesses of the solution
  • Suggestions for improvement
  • Comparative analysis with top-performing submissions (anonymized)

Real-time Collaboration

AI enhances team collaboration through several features:

Automated Task Suggestions

  • Algorithm: Uses natural language processing to analyze project requirements and team member profiles.
  • Implementation: Integrates with project management tools via APIs to suggest task allocations based on skills and workload.

Intelligent Code Correction

  • Real-time Analysis: AI continuously analyzes code as it's written, suggesting improvements and catching potential bugs.
  • Integration: Implemented as a VS Code extension that communicates with our AI backend for real-time suggestions.

Conflict Resolution

  • Merge Conflict Assistance: AI analyzes conflicting code changes and suggests optimal resolutions.
  • Implementation: Integrated with Git workflows, providing AI-powered suggestions during merge processes.

Dynamic Leaderboards

Our leaderboard system updates in real-time as challenges are solved and evaluated.

Technical Approach

  1. API Integration: RESTful API endpoints for submitting scores and retrieving leaderboard data.
  2. WebSocket Communication: Real-time updates pushed to clients using WebSocket protocol.
  3. Caching Layer: Redis used for caching leaderboard data to ensure fast retrieval and updates.

Ranking Algorithm

  • Utilizes an Elo-inspired rating system, adapted for coding challenges.
  • Factors in challenge difficulty, solving time, and code quality scores.

Implementation Details

  • Backend: Node.js with Express for API endpoints and Socket.io for WebSocket communication.
  • Database: PostgreSQL for persistent storage of user scores and challenge data.
  • Caching: Redis for in-memory caching of current leaderboard state.

Skill Assessment

Our AI-powered skill assessment system provides detailed insights into each participant's coding abilities.

Analysis Components

  1. Coding Style Analysis: Evaluates consistency, readability, and adherence to best practices.
  2. Pattern Detection: Identifies common coding patterns and assesses their appropriateness.
  3. Efficiency Metrics: Analyzes time and space complexity of solutions.
  4. Language Proficiency: Assesses mastery of language-specific features and idioms.

Technical Implementation

  • OpenAI Integration: Utilizes GPT-4 for natural language analysis of code comments and documentation.
  • Custom ML Models: Trained on a large corpus of code to detect patterns and assess efficiency.
  • Static Code Analysis: Incorporates tools like ESLint and Pylint for language-specific analysis.

Feedback Generation

  • Generates a comprehensive skill report after each challenge.
  • Provides personalized improvement suggestions and learning resources.
  • Tracks progress over time, highlighting areas of improvement and newly acquired skills.

API Integration

  • RESTful API endpoints for submitting code for analysis and retrieving skill assessment reports.
  • Webhook support for integrating skill assessments into external learning management systems or IDEs.

By leveraging these AI-powered features, the AI Hacking League provides a unique, engaging, and educational competitive coding experience that continuously adapts and improves based on participant interactions and performance.

@ThibaultMardinli
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Dope !

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