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Office Address

123/A, Miranda City Likaoli
Prikano, Dope

Phone Number

+0989 7876 9865 9

+(090) 8765 86543 85

Email Address

info@example.com

example.mail@hum.com

Empowering Solutions with Graphite

With Bittensor as our foundation, our team developed Graphite to tackle real world problems with decentralized applications

The problem we are solving

The problem we are solving

ComplexityNP-Hard
ApplicationsLogistics, Operations and more
EfficiencyUp to 7% improvement

Our focus on solving graph-based problems starts with the Traveling Salesman Problem (TSP), a benchmark in route optimization. Building on this, we tackle advanced challenges like the multi-Traveling Salesman Problem (mTSP) and the multi-depot mTSP (mDmTSP), showcasing our expertise in complex graph optimization and driving innovation in this space.

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Miners

Miners

Active Miners230+
Avg Reward0.2τ / day
Response Rate100%

Our miners train machine learning models and submit their answers on our Graphite subnet, specializing in solving complex graphical problems like the Traveling Salesman Problem (TSP). By dedicating computational resources to optimize these algorithms, they enhance the subnet’s efficiency and scalability while earning TAO rewards for their contributions.

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Validators

Validators

Validation Speed~30s
Accuracy100%
Network SecurityBlockchain Secure

Our validators on the Graphite subnet ensure the quality and reliability of machine learning models solving graphical problems like the Traveling Salesman Problem. By evaluating miner outputs and promoting the best-performing algorithms, they maintain the subnet’s integrity and earn TAO rewards for safeguarding its excellence.

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Graphite's Performance

Subnet 43 Top Solution Benchmarks: mdMTSP

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Our Roadmap

Phase 1

Carbon

We will undertake comprehensive infrastructure upgrades to establish a robust and scalable foundation for our ecosystem. Our team will meticulously refine the rewards mechanism, ensuring that incentives are both fair and motivating for all participants. We are committed to enhancing consumer and client support on the frontend, providing an intuitive and seamless user experience. Transparency is at the core of our vision, which is why we will implement public and transparent performance logging and ranking systems. This phase sets the stage for a resilient and user-centric platform, paving the way for future innovations.

Phase 2a

Graphene

We will focus on developing an advanced incentive mechanism and a dynamic bounty system designed to encourage the resolution of complex graph problems. By fostering a collaborative environment, we aim to attract top talent and drive continuous innovation within our community. We will significantly improve our documentation and provide comprehensive educational resources to accelerate subnet improvements, ensuring that developers have the tools they need to succeed. This phase is dedicated to building a strong foundation for subnet advancements, promoting knowledge sharing and collective growth. Our vision is to create a vibrant ecosystem where problem-solving and education go hand in hand to propel our technology forward.

Phase 2b

Graphyne

We will launch the commercial subnet API, empowering validators to monetize their bandwidth and contribute more effectively to the network’s operations. This initiative will open new revenue streams and incentivize validators to increase their participation and investment in the subnet. We will also foster intra-subnet competition to rigorously test product-market fit, ensuring that our solutions meet the highest standards and address real-world needs. By encouraging healthy competition, we aim to drive excellence and innovation within our network. This phase is crucial for scaling our operations and validating our market strategies, setting the stage for widespread adoption.

The Bittensor Ecosystem

Miners

Miners power the Bittensor ecosystem by dedicating computational resources to train decentralized AI models, improving their performance and solving real-world problems. They earn TAO rewards based on the quality and relevance of their contributions, driving innovation in open and collaborative machine learning.

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Validators

Validators ensure the integrity of the network by evaluating miner outputs, promoting only high-quality models, and maintaining fairness. They play a crucial role in quality control and consensus building, earning TAO rewards for safeguarding the ecosystem’s trust and reliability.