Round 1 Winners!
Proof of Usefulness Report

Int. Conference on Machine Learning

Analysis completed on 3/18/2026

-34.5
Proof of Usefulness Score
Lab Mode

The submission is flagged as highly suspicious and likely fraudulent. While the International Conference on Machine Learning (ICML) is a legitimate and prestigious event, the submitter ('MysticStorm') uses a fabricated email and provides nonsensical claims ('Electrical & Electronic Manufacturing', 'all time marketcap: 2500000', 'most people have used my product'). Per the calibration guidelines, severe penalties are applied for red flags and lack of verifiable traction from the submitter, resulting in a negative score.

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Score Breakdown

Real World Utility-5
Audience Reach Impact-5
Technical Innovation-5
Evidence Of Traction-12.5
Market Timing Relevance+0
Functional Completeness-2.5
Subtotal-30
Usefulness Multiplierx1.15
Final Score-34

Project Details

Project URL
Description
The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

Algorithm Insights

Market Position
Early stage requiring focused development
User Engagement
Documented reach suggests active user community
Technical Stack
Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline