ProphetVision: The AI-Powered Video Archive

ProphetVision draws inspiration from 'Metropolis' by uncovering hidden value in overlooked areas and the potential for social stratification within video content. It's also inspired by 'Hyperion', creating layers of mystery and discovery for users as they explore the platform's unique offerings. And It leverages insights from the 'AI Workflow for Companies' scraper project, using AI to analyze video data to predict future trends. The core concept is a video platform focusing on under-appreciated or obscure content – videos with high potential but low visibility on mainstream platforms (e.g., niche tutorials, independent films, archived footage).

Story: In a media landscape dominated by algorithms optimizing for engagement above all else, genuinely valuable content is often buried. ProphetVision aims to unearth these 'hidden gems', guided by AI algorithms acting as 'prophets' predicting future trends based on past performance and current cultural shifts. The platform's interface will have a slightly retro, almost mystical aesthetic, emphasizing discovery and serendipity.

Concept:
1. Data Scraping & Analysis: Initially, the 'AI Workflow' scraper would be adapted to collect data on videos from various sources: niche subreddits, independent creator platforms (e.g., Vimeo, PeerTube), archival websites, and even YouTube's less-trafficked corners. The AI will focus not just on views, but on other metrics like comment sentiment, topic novelty, and viewer retention relative to content length.
2. Trend Prediction: The AI will use machine learning models (e.g., time series analysis, natural language processing) to predict future trends based on the collected data. It will identify topics or styles that are gaining traction but haven't yet exploded into the mainstream.
3. Curated Recommendations: ProphetVision will offer users personalized recommendations based on their viewing history and the AI's trend predictions. The recommendations will emphasize obscure, high-potential content that users might not find elsewhere.
4. Creator Discovery: The platform will feature a section showcasing creators whose videos have been identified as high-potential by the AI. This will give creators a boost in visibility and help them connect with a more targeted audience.

How it Works:
1. Initial Implementation: Start with a simple platform built on readily available open-source video player and framework. Focus on building the AI data pipeline and prediction models first.
2. Content Acquisition: Initially, rely on scraping and linking to existing content on other platforms (YouTube embedding, Vimeo integration, etc.). This minimizes storage costs.
3. Monetization: Implement a tiered subscription model for premium features like personalized recommendations and ad-free viewing. Partner with niche brands for targeted advertising. Offer creators opportunities to monetize their content through revenue sharing.

Niche, Low-Cost, High Earning Potential:
- Niche: Focuses on a specific segment of the video market: under-appreciated and obscure content.
- Low-Cost: Leveraging existing open-source tools and focusing on data scraping instead of original content creation keeps costs down.
- High Earning Potential: Capturing the attention of users interested in niche content and providing value to undiscovered creators opens up opportunities for subscription revenue and targeted advertising.