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<!DOCTYPE html>
<html lang="en">
<head>
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logo-src="https://openmined.org/wp-content/uploads/2024/11/logo-1@2x.png"
logo-text="OpenMined"
current-page="protocol"
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<!-- Hero Section -->
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<div class="hero-text">
<h1 style="font-size: 2.5rem; margin-top: 2rem; margin-bottom: 2rem; line-height: 1.2;">Federating AI with <br>Attribution-Based Control</h1>
<p class="hero-subtitle" style="font-size: 1.1rem; margin: 0 0 2rem 0; line-height: 1.5;">
Learn how the Syft protocol and ecosystem can make AI both more powerful and more inclusive
</p>
</div>
</div>
</div>
</section>
<!-- Structural Problem Section -->
<section style="background: var(--color-bg-light); padding: 3rem 0;">
<div class="container" style="max-width: 1000px;">
<div style="text-align: center; margin-bottom: 3rem;">
<h2 style="font-size: 1.8rem; margin-bottom: 1.5rem; color: var(--color-accent); font-weight: 500; letter-spacing: -0.5px;">The Structural Problem with AI</h2>
<p style="font-size: 1rem; line-height: 1.6; max-width: 700px; margin: 0 auto; color: var(--text-primary); font-weight: 300;">
There's <span style="font-weight: 500;">3,000x</span> more human-data generated each year than what LLMs use. Yet, most of it never makes it into AI and data owners are even opting out en masse. The issue: existing AI architectures structurally prevent meaningful incentive creation. Here's why:
</p>
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<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 2rem; margin-bottom: 3rem;">
<!-- Problem 1: Addition -->
<div style="background: var(--card-bg); border: 1px solid var(--color-secondary-contrast); padding: 1.5rem; border-radius: 8px; box-shadow: var(--shadow);">
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</div>
<h3 style="font-size: 1.1rem; margin: 0; font-weight: 500; color: var(--color-secondary);">Addition Problem</h3>
<p style="font-size: 0.85rem; margin: 0.25rem 0 0 0; color: var(--text-secondary); font-weight: 400;">The Technical Problem</p>
</div>
<p style="font-size: 0.9rem; line-height: 1.5; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
Deep learning is like a giant blender. Your content gets mathematically "mixed" with everything else during training steps, becoming impossible to separate.
<br></br>You can't enforce rules because the AI can't tell which parts of its knowledge came from you.
</p>
</div>
<!-- Problem 2: Use Bundling -->
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</div>
<h3 style="font-size: 1.1rem; margin: 0; font-weight: 500; color: var(--color-accent);">Use Bundling</h3>
<p style="font-size: 0.85rem; margin: 0.25rem 0 0 0; color: var(--text-secondary); font-weight: 400;">The Business Problem</p>
</div>
<p style="font-size: 0.9rem; line-height: 1.5; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
You can't say "yes, use my stories to help students with creative writing, but no, don't use them to generate competing stories.". <br></br> Opting into AI is now all-or-nothing: you either support <em>every</em> possible AI prediction, or none at all.
</p>
</div>
</div>
<div style="display: grid; grid-template-columns: 1fr 1fr; gap: 3rem; align-items: center; background: var(--glass-light, rgba(255, 255, 255, 0.8)); padding: 2.5rem; border-radius: 12px; border: 1px solid var(--glass-border, rgba(255, 255, 255, 0.2)); margin-bottom: 2rem;">
<div>
<p style="font-size: 1rem; margin-bottom: 1.5rem; color: var(--text-primary); font-weight: 400; letter-spacing: -0.2px;">
<span style="background: linear-gradient(135deg, var(--color-accent), var(--color-secondary)); -webkit-background-clip: text; -webkit-text-fill-color: transparent; background-clip: text; font-weight: 500;">Attribution-Based Control</span> solves this by:
</p>
<div style="display: flex; flex-direction: column; gap: 1.5rem;">
<div>
<p style="font-size: 0.9rem; line-height: 1.6; margin: 0; color: var(--text-primary); font-weight: 300;">
<span style="color: var(--color-accent); font-weight: 400;">•</span> <strong style="font-weight: 400;">Separable architecture:</strong> your data remains in your control, minimising memorisation during training (if any) and using it effectively at prediction time.
</p>
</div>
<div>
<p style="font-size: 0.9rem; line-height: 1.6; margin: 0; color: var(--text-primary); font-weight: 300;">
<span style="color: var(--color-secondary); font-weight: 400;">•</span> <strong style="font-weight: 400;">Live querying</strong> where AI asks permission in real-time, letting you enforce preferences at use time.
</p>
</div>
</div>
</div>
<div style="text-align: center;">
<img src="./src/assets/OpenMined Live Graphics (3).png" alt="Attribution-Based Control Diagram" style="width: 100%; height: auto; border-radius: 12px;" />
</div>
</div>
</div>
</section>
<!-- How It Works -->
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<div style="text-align: center; margin-bottom: 3rem;">
<h2 style="font-size: 1.8rem; margin-bottom: 1.5rem; color: var(--text-primary); font-weight: 500; letter-spacing: -0.5px;">How It Works</h2>
<p style="font-size: 1rem; line-height: 1.6; max-width: 700px; margin: 0 auto; color: var(--text-secondary); font-weight: 300;">
Different model architectures can enable Attribution-Based Control, keeping your knowledge separable and queryable at use time.
</p>
</div>
<!-- ABC-Enabling Architectures -->
<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(280px, 1fr)); gap: 1.5rem; margin-bottom: 3rem;">
<!-- RAG -->
<div style="background: var(--glass-light, rgba(255, 255, 255, 0.05)); padding: 1.25rem; border-radius: 8px; border-left: 3px solid var(--color-accent);">
<h3 style="font-size: 1rem; margin-bottom: 0.5rem; color: var(--color-accent); font-weight: 500;">Federated <br>Retrieval-Augmented Generation</h3>
<p style="font-size: 0.85rem; line-height: 1.5; margin: 0; color: var(--text-primary); font-weight: 300;">
Uses external knowledge sources that are queried in real time and added to the model’s responses, while keeping full attribution to the original sources.
</p>
</div>
<!-- MoE -->
<div style="background: var(--glass-light, rgba(255, 255, 255, 0.05)); padding: 1.25rem; border-radius: 8px; border-left: 3px solid var(--color-secondary);">
<h3 style="font-size: 1rem; margin-bottom: 0.5rem; color: var(--color-secondary); font-weight: 500;">Federated <br>Mixture of Experts</h3>
<p style="font-size: 0.85rem; line-height: 1.5; margin: 0; color: var(--text-primary); font-weight: 300;">
Each participant keeps their own local model, which contributes predictions that are combined (like a voting system) to improve overall performance.
</p>
</div>
<!-- Hybrid -->
<div style="background: var(--glass-light, rgba(255, 255, 255, 0.05)); padding: 1.25rem; border-radius: 8px; border-left: 3px solid var(--primary);">
<h3 style="font-size: 1rem; margin-bottom: 0.5rem; color: var(--primary); font-weight: 500;">Hybrid Architectures</h3>
<p style="font-size: 0.85rem; line-height: 1.5; margin: 0; color: var(--text-primary); font-weight: 300;">
Federated systems that keep data partly separate while combining multiple compatible methods, such as privacy-preserving training (e.g., differential privacy) with FedRAG, FlexOlmo, and similar approaches.</p>
</div>
</div>
</div>
</section>
<!-- Federated RAG Deep Dive -->
<section style="padding: 3rem 0;">
<div class="container" style="max-width: 80%; background-color: var(--card-bg); box-shadow: var(--shadow-lg); border-radius: 6px;"><br></br>
<div style="text-align: center; margin-bottom: 3rem;">
<h2 style="font-size: 1.8rem; margin-bottom: 1rem; color: var(--color-secondary); font-weight: 500; letter-spacing: -0.5px;">Deep Dive: Federated RAG in Syft</h2>
<img src="./src/assets/overview_fedrag.png" alt="Federated RAG Overview" style="max-width: 700px; width: 100%; height: auto; border-radius: 12px;" />
</div>
<!-- Step Carousel -->
<div id="federated-rag-steps" style="position: relative; border-radius: 12px; padding-bottom: 2rem; padding-left:4rem; padding-right:4rem;">
<!-- All Steps Overview -->
<div style="display: flex; justify-content: center; gap: 1rem; margin-bottom: 2rem; flex-wrap: wrap;">
<div class="step-overview active-overview" data-step="1" style="background: var(--color-accent); color: white; padding: 0.5rem 1rem; border-radius: 6px; font-size: 0.8rem; font-weight: 500; cursor: pointer; transition: all 0.3s ease;" onclick="goToStep(1)">1. Local Data Processing</div>
<div class="step-overview" data-step="2" style="background: var(--glass-border, rgba(255, 255, 255, 0.3)); color: var(--text-secondary); padding: 0.5rem 1rem; border-radius: 6px; font-size: 0.8rem; font-weight: 500; cursor: pointer; transition: all 0.3s ease; opacity: 0.6;" onclick="goToStep(2)">2. Directed Query</div>
<div class="step-overview" data-step="3" style="background: var(--glass-border, rgba(255, 255, 255, 0.3)); color: var(--text-secondary); padding: 0.5rem 1rem; border-radius: 6px; font-size: 0.8rem; font-weight: 500; cursor: pointer; transition: all 0.3s ease; opacity: 0.6;" onclick="goToStep(3)">3. Policy Enforcement</div>
<div class="step-overview" data-step="4" style="background: var(--glass-border, rgba(255, 255, 255, 0.3)); color: var(--text-secondary); padding: 0.5rem 1rem; border-radius: 6px; font-size: 0.8rem; font-weight: 500; cursor: pointer; transition: all 0.3s ease; opacity: 0.6;" onclick="goToStep(4)">4. Secure LLM Aggregation</div>
</div>
<!-- Step Content Container -->
<div id="step-content" style="min-height: 300px;">
<!-- Step 1: Local Indexing -->
<div class="step-slide active" data-step="1">
<div style="display: flex; align-items: center; gap: 2rem;">
<div style="flex: 1;">
<div style="display: flex; align-items: center; margin-bottom: 1rem;">
<div style="background: var(--color-accent); color: white; width: 32px; height: 32px; border-radius: 50%; display: flex; align-items: center; justify-content: center; font-weight: bold; margin-right: 1rem;">1</div>
<h3 style="font-size: 1.2rem; margin: 0; color: var(--text-primary); font-weight: 500;">Local Data Processing</h3>
</div>
<p style="font-size: 0.9rem; line-height: 1.6; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
Each data owner creates private vector databases at their datasite, embedding their content locally to preserve control.
</p>
<ul style="font-size: 0.85rem; line-height: 1.5; color: var(--text-secondary); font-weight: 300; margin: 0; padding-left: 1.5rem;">
<li>Content stays at source: never copied centrally</li>
<li>Data owner can decide policies for querying and release of responses</li>
</ul>
</div>
<div style="flex: 0 0 500px;">
<img src="./src/assets/local_indexing.png" alt="Local Indexing Diagram" style="width: 100%; height: auto; border-radius: 8px;" />
</div>
</div>
</div>
<!-- Step 2: Directed Query -->
<div class="step-slide" data-step="2">
<div style="display: flex; align-items: center; gap: 2rem;">
<div style="flex: 1;">
<div style="display: flex; align-items: center; margin-bottom: 1rem;">
<div style="background: var(--color-secondary); color: white; width: 32px; height: 32px; border-radius: 50%; display: flex; align-items: center; justify-content: center; font-weight: bold; margin-right: 1rem;">2</div>
<h3 style="font-size: 1.2rem; margin: 0; color: var(--text-primary); font-weight: 500;">Directed Query</h3>
</div>
<p style="font-size: 0.9rem; line-height: 1.6; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
End-users select specific data sources for their query, giving them control over which sources they want to rely upon.
</p>
<ul style="font-size: 0.85rem; line-height: 1.5; color: var(--text-secondary); font-weight: 300; margin: 0; padding-left: 1.5rem;">
<li>User chooses: "News Outlet A, B, and F"</li>
<li>Query routed only to selected datasites</li>
</ul>
</div>
<div style="flex: 0 0 500px;">
<img src="./src/assets/query_submission.png" alt="Query Submission Diagram" style="width: 100%; height: auto; border-radius: 8px;" />
</div>
</div>
</div>
<!-- Step 3: Policy Enforcement -->
<div class="step-slide" data-step="3">
<div style="display: flex; align-items: center; gap: 2rem;">
<div style="flex: 1;">
<div style="display: flex; align-items: center; margin-bottom: 1rem;">
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<h3 style="font-size: 1.2rem; margin: 0; color: var(--text-primary); font-weight: 500;">Policy Enforcement</h3>
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<p style="font-size: 0.9rem; line-height: 1.6; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
When a query is received, the preferences are enforced in real-time. Input policies decide who can use your content and output policies about what information is released.
</p>
<ul style="font-size: 0.85rem; line-height: 1.5; color: var(--text-secondary); font-weight: 300; margin: 0; padding-left: 1.5rem;">
<li>Rate limiting, access controls</li>
<li>Human-in-the-loop review if needed</li>
<li>LLM filters for privacy protection</li>
<li>Monetization</li>
</ul>
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<img src="./src/assets/policies.png" alt="Policy Enforcement Diagram" style="width: 100%; height: auto; border-radius: 8px;" />
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<h3 style="font-size: 1.2rem; margin: 0; color: var(--text-primary); font-weight: 500;">Secure Aggregation</h3>
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Results are combined through concatenation, while preserving source attribution. If concerns over confidentiality of outputs, a secure aggregation can be used (as opposed to using remote LLMs).
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<li>Local LLMs process at each source</li>
<li>Trusted Execution Environments for multi-source</li>
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<h2 style="font-size: 1.8rem; margin-bottom: 1.5rem; color: var(--color-accent); font-weight: 500; letter-spacing: -0.5px;">Explore the Syft Protocol & Tools</h2>
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A complete toolkit for implementing Attribution-Based Control whenever your data is to used by AI.
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<h3 style="font-size: 1rem; margin: 0; color: var(--primary); font-weight: 500;">Syft & SyftBox</h3>
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Live networked architecture, that enables secure communication, data sharing (like a massive shared DropBox with access permissions), and identity-based access.
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<i class="fas fa-book" style="margin-right: 0.25rem;"></i> Documentation
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<i class="fas fa-rocket" style="margin-right: 0.25rem;"></i> Quick Start
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<p style="font-size: 0.8rem; margin: 0; color: var(--text-secondary); font-weight: 300;">Local AI Service & Policy Enforcement</p>
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</div>
<p style="font-size: 0.85rem; line-height: 1.5; margin-bottom: 1rem; color: var(--text-primary); font-weight: 300;">
Local runtime for creating and managing endpoints, with many off-the-shelf pre-packaged integrations. This is also where policies can be defined or used.
</p>
<a href="./syft-router/index.html" style="font-size: 0.8rem; color: var(--secondary); text-decoration: none; font-weight: 400; margin-right: 1rem;">
<i class="fas fa-book" style="margin-right: 0.25rem;"></i> Documentation
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<i class="fas fa-rocket" style="margin-right: 0.25rem;"></i> Github
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<p style="font-size: 0.8rem; margin: 0; color: var(--text-secondary); font-weight: 300;">Dev Tools</p>
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Using a highly convenient Python SDK, you can explore the Federated AI Network, query any data source and get with ease state-of-the-art results.
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<i class="fas fa-book" style="margin-right: 0.25rem;"></i> Documentation
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<a href="https://github.com/OpenMined/syft-nsai-sdk" style="font-size: 0.8rem; color: var(--color-accent); text-decoration: none; font-weight: 400;">
<i class="fas fa-rocket" style="margin-right: 0.25rem;"></i> Github
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<p style="font-size: 0.8rem; margin: 0; color: var(--text-secondary); font-weight: 300;">Agentic Tools</p>
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Use SyftMCP to get insights from this network with ease.
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<i class="fas fa-clock" style="margin-right: 0.25rem;"></i> Coming Soon
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The Syft Protocol and its tools illustrations.
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The future of AI depends on collaboration among those who share a common mission.<br><br>Join the conversation and help shape what comes next.
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