Add Common Compute Network grant application#2737
Conversation
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Hi @w0w I'm not seeing anything in the application regarding DOT or how it would be used in the system? Can you further elaborate? |
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Thank you for the application and the interest in building on Polkadot, @w0w. However, the Web3 Foundation decided to shut down the original Grants Program to focus on products aligning with our newest guidelines. Following these guidelines, we are looking for teams with a proven track record building on very specific issues with a product-mindset. I'm afraid edge AI is not one of those issues. I am therefore going to close this PR. Feel free to check out the new Kusama Vision program instead: https://x.com/Zendetta/status/2011414901374451777. In any case, I wish you best of luck. |
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@semuelle Thanks for response and updtate, I will look into Kusama program. @keeganquigley Sorry I was away from dev and just resumed today from a digital detox, I believe the PR is closed but will share in brief what application of DOT ( token/blockchain ) i am working on - Nodes running AI models provide inference and token usage on each node is stored on an immutable ledger ( perhaps it may evolve into its own parachain as network grows ) the uptime, availability, health checks are non monetary datasets which needs to be on chain for transparency on node usage/performance and the payouts to be executed on chain with wallets attached to each node. I am not sure if it fits but this is so far my understanding coming from web2/hardware background. |
Project Abstract
Project Abstract
Common Compute Network is a decentralized infrastructure protocol that transforms edge devices into a distributed AI inference network with economic incentives built on Polkadot. The project extends the existing Common Compute OS (production-ready and deployed) to create a tokenized network where compute providers earn rewards for serving AI inference requests. Our architecture uses Substrate pallets for transparent coordination (device registry, job intents metadata) while keeping AI inference off-chain via gateway and device agents. This approach delivers a practical path from single-device inference to a networked system without on-chain computation overhead.
Grant level
Application Checklist
project_name.md).