> ## Documentation Index
> Fetch the complete documentation index at: https://docs.jpeg.fun/llms.txt
> Use this file to discover all available pages before exploring further.

# Whitepaper

> Complete technical whitepaper for JPEG

## JPEG Whitepaper Version 2.2

**Authors:** Danny Vayne & Lim Keng Hin\
**Date:** November 2025

## Abstract

Billions of JPEGs are taken every day. What if taking one could make you money? **JPEG** is a social prediction game blending BeReal-style photo sharing with market-based coordination, powered by Base (Ethereum Layer 2). Users submit photos for daily themes, earning PX (Pixels), while others collect them to predict the day's most resonant image. Earlier collects receive more shares but carry higher risk, creating a strategic market for attention.

Inspired by Polymarket, JPEG introduces **"True Social"**, where attention is backed by capital and rewards flow transparently to creators. Beyond the application, JPEG is designed to evolve into an open, composable network where JPEGs become standard photo assets that can be owned, traded, and built on by developers, entrepreneurs, traders, and collectors. This paper explores JPEG's mechanics, incentives, behavioral foundations, and long-term potential as both a viral consumer product and a creative economic network.

## Download the Complete Whitepaper

**Not available**

## Table of Contents

The complete whitepaper covers:

1. **Introduction** - Vision and core mechanics
2. **The Social Prediction Game** - How JPEG works
3. **Open Networks, Skeuomorphism, and Digital Ownership** - Platform vs. network dynamics, blockchain advantages
4. **The JPEG Network** - Evolution from app to composable photo asset network
5. **Types of Users** - Creator and speculator personas, A-to-B transition
6. **Mathematical Modeling & Tokenomics** - Shares-for-Fees model, time decay formulas, prize pool mechanics
7. **Behavioral Economics** - Loss aversion, social proof, endowment effect, intrinsic vs. extrinsic motivation
8. **Game Theory** - Strategic behavior, prediction market dynamics, decision matrices
9. **User Acquisition and Retention** - Growth strategies, community building through tags
10. **Development Stages** - Beta, points removal, B2B integration
11. **Data and Validation** - Metrics and projections
12. **Future Plans** - Data annotation, dual token system
13. **B2B Potential** - Brand partnerships and UGC engine
14. **Legal, Data Rights & Ethical Considerations** - Photo ownership, privacy, GDPR compliance
15. **Risks and Mitigation** - Platform safeguards
16. **Conclusion** - Summary and vision

## Key Highlights

### Innovation

JPEG's innovation lies in its **"True Social"** concept, inspired by Polymarket's capital-backed prediction model. Capital flows through collects reveal the truth of creative resonance—the most compelling photos rise to the top, ensuring fair rewards.

Beyond the application, JPEG is designed to evolve into an **open, composable network** where JPEGs become standard photo assets that can be owned, traded, and built upon by developers, entrepreneurs, traders, and collectors. This network approach distinguishes JPEG from traditional platforms: platforms compete with complements, networks empower them.

### Economic Model

**Shares-for-Fees Model:**
The JPEG economy operates on a **Shares-for-Fees** model, ensuring 100% of the PX (Pixel) currency deposited by users is immediately allocated to the global prize pool. Platform and creator fees are paid in the form of shares, introducing controlled dilution to winning potential rather than reducing capital available for rewards. This mechanism guarantees capital efficiency and full transparency.

**Dual Token System:**

* **Pixels (PX):** An in-game token used for themed collects and freestyle purchases, designed to feel non-financialized for users
* \*\*$JPEG:** A governance token for investors, enabling speculation on the platform's success. Profits from the app are reinvested to create deflationary pressure on $JPEG

**Share Allocation:**

* **User Shares:** Collectors receive shares based on bet amount and time discount: (S = B \cdot (1 + D\_t))
* **Creator Shares:** Photo creators receive shares as royalties: (S\_C = B \cdot R\_C) (typically 20%)
* **Foundation Shares:** JPEG Foundation receives shares: (S\_F = B \cdot R\_F) (typically 10%)
* **Freestyle JPEGs:** 100% direct sales to creators

### Platform Statistics

* **Waitlist:** 220,000+ signups (as of October 2025)
* **Beta Engagement Uplift:** 10-15% (with quests and milestones)
* **Referral DAU Increase:** 15% (beta tests)
* **Target Stage 2 DAU:** 1,500-3,000

### Research Foundation

The whitepaper draws from:

* Behavioral economics (loss aversion, social proof, endowment effect)
* Game theory (non-cooperative games, strategic behavior)
* Prospect theory and self-determination theory
* NFT market analogies and SocialFi trends
* Network theory and composability (Dixon 2024: "Read Write Own")
* Skeuomorphic design principles for blockchain adoption

## Disclaimer

<Warning>
  **Restricted Access:** This whitepaper is not ready for public disbursement
  and is intended solely for individuals within the organization, investors, and
  permissioned individuals. Distribution beyond these parties is prohibited
  without explicit authorization.
</Warning>

## Citation

If referencing this whitepaper:

```
Vayne, D., & Lim, K. H. (2025). JPEG: A Social Game Integrating Photo Sharing,
Prediction Markets, and Network for Composable Photo Assets (Version 2.2).
JPEG Platform.
```

## Questions?

For questions about the whitepaper or JPEG platform:

* **Email:** [support@jpeg.fun](mailto:support@jpeg.fun)
* **Website:** [jpeg.fun](https://jpeg.fun)
* **Documentation:** Browse all documentation pages

<Note>
  The whitepaper is a living document and may be updated based on platform
  development, user feedback, and market conditions. Check back for the latest
  version.
</Note>