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Overview

The AI Studio integrates with Kyne’s decentralized infrastructure, enabling developers to build and deploy AI models with native blockchain capabilities. Leveraging Sui for transparent operations and Walrus for efficient model distribution.

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Key Benefits

For Model Creators

  • • Token-based incentive systems
  • • Transparent usage analytics
  • • Automated distribution mechanisms
  • • Built-in collaboration tools

For Tool Builders

  • • Decentralized compute access
  • • Granular access controls
  • • Walrus-powered distribution
  • • Native marketplace integration

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Architecture

Compute Layer

  • • Distributed training nodes
  • • Dynamic resource allocation
  • • Byzantine fault tolerance
  • • Verifiable computations

Storage Layer

  • • Walrus integration
  • • Red Stuff encoding
  • • Minimal replication factor
  • • Provable availability

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Getting Started

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Quick Start

from kyne.tools import AIToolkit
from kyne.wallet import KyneWallet

# Initialize with wallet
toolkit = AIToolkit(
    wallet=SUIWallet.from_private_key("0x..."),
    config={
        "storage": "walrus",
        "compute": "distributed"
    }
)

# Deploy model
deployment = await toolkit.deploy_model(
    model_path="./my_model",
    compute_config={
        "availability": "high",
        "distribution": "global"
    }
)

# Monitor metrics
stats = await deployment.get_stats()
print(f"Active nodes: {stats.compute_nodes}")
print(f"Storage health: {stats.availability_score}")

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Training Pipeline

Reserve Resources

# Reserve compute resources
reservation = await toolkit.reserve_training(
    gpu_type="a100",
    duration_hours=24,
    priority="standard"
)

Train Model

# Start training with marketplace integration
training_job = await toolkit.train_model(
    dataset_id="0x...",  # From marketplace
    config={
        "share_checkpoints": True,
        "compute_priority": "high"
    }
)

Deploy & Monitor

# Deploy with resource configuration
deployment = await training_job.deploy(
    config={
        "availability": "high",
        "distribution": "global",
        "compute_tier": "standard"
    }
)

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Resource Management

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Access Tiers

Resource Allocation

compute_tiers:
  standard:
    features:
      - Basic GPU allocation
      - Standard availability
  priority:
    features:
      - Priority GPU access
      - High availability
      - Advanced monitoring

Distribution

distribution_config:
  replication_factor: 4.5
  availability_target: 99.9%
  
fault_tolerance:
  node_failures: 33%
  recovery_time: automatic

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Resource Optimization

Smart Allocation

  • Dynamic resource scaling
  • Automated load balancing
  • Efficient shard distribution

Performance Tuning

  • Compute optimization
  • Automatic scaling
  • Storage efficiency

Availability

  • Byzantine fault tolerance
  • Distributed recovery
  • Verifiable computations

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Security & Compliance

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Access Control

Access Management

  • • Role-based permissions
  • • Resource quotas
  • • API key management
  • • Usage monitoring

Model Protection

  • • Encrypted storage
  • • Access logging
  • • Integrity verification
  • • Audit trails

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Infrastructure Security

  • Isolated training environments
  • Secure model deployment
  • Resource monitoring
  • Verifiable computations
  • Walrus Red Stuff encoding
  • Byzantine fault tolerance
  • Proof verification
  • Distributed access control

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Next Up

Data Contributors

Learn how to contribute data and earn rewards through the Kyne network.

Data Owners

Discover how to manage, monetize, and protect your AI datasets.
Kyne creates value for both data contributors and owners by providing secure infrastructure and clear incentives for quality AI data.