Pranav Deshmane@Phdeshmane

Valen-timer is a fast-paced web game where players select AI digital twins, get matched via preference graphs, and plan virtual dates—scoring on simulated success. Beyond entertainment, it trains AI systems in human connection through gameplay. Gameplay: Players choose from diverse AI twins with unique personalities. A matching algorithm analyzes compatibility across traits and interests. Players rapidly plan date routes—selecting venues and conversation flows against the clock. Coffee shops for intimacy, galleries for culture, arcades for playfulness. Each choice impacts success. Real-Time Engagement Tracking: The platform highlights exactly what works and fails during interactions: Small Talk Analysis shows: Ice breaker effectiveness ("How's your day?" scores 2/10 vs. "Ever hiked coastal trails?" at 8/10) Question balance (avoiding interrogation mode) Humor landing rates Shared interest discovery moments Topic transition smoothness Deep Conversation Metrics track: Vulnerability matching and emotional reciprocity Value alignment reveals Empathy response quality Venue-Specific Performance: Coffee shops excel for intimate exchanges, activity venues spike during competition but drop if conversation suffers. Micro-Moment Highlights: Remembering earlier details (+15% engagement), perfect compliment timing, or awkward transitions (-25% engagement). Post-date breakdowns show: "Your pottery hobby question increased engagement 40%. Switching topics without transition dropped engagement 25%." The system pinpoints exact peaks and valleys. AI Training Impact: Every date trains agentic AI systems in social intelligence—emotional responses, preference inference, adaptive strategies. This scales social robotics training for customer service bots, therapeutic companions, and educational tutors. Valen-timer merges gaming with AI research—players enjoy speed-dating while training machines to understand human connection.

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