dApps
Apr 12, 2025
Pluralis Protocol Learning Compute Allowlist
How to Join the Decentralized AI Training Revolution
The Next Big Thing in Decentralized AI Training
Pluralis Research is pioneering "Protocol Learning" - a revolutionary approach that allows users to contribute computing power to train AI models collectively over the internet.
Contributors will be rewarded for participating, though specific details haven't been disclosed yet. The most important thing to know is that Pluralis is currently accepting applications for their compute allowlist, and only approved participants can join the initial phase.
What is Pluralis Protocol Learning?
Pluralis Research is developing Protocol Learning as an alternative to today's AI landscape, which is dominated by either closed proprietary models or economically unsustainable open-source initiatives.
Their approach enables collaborative model training by:
Pooling computational resources across multiple participants
Ensuring no single entity can obtain the complete model
Creating economic incentives for contributors without requiring upfront costs
The most fascinating aspect is their work on solving what many consider an impossible problem: low-bandwidth, model-parallel training. This technical challenge, if solved, could fundamentally change how AI models are developed.
Fundraise Announcements
Pluralis recently raised a $7.6 million seed round led by USV and Coinfund. This substantial early funding indicates strong investor confidence in their approach and team.
Why is it important now?
The current AI training landscape requires massive computational resources controlled by a few large companies. Pluralis is attempting to democratize this process, similar to how blockchain technology has decentralized finance.
How to Get on the Pluralis Compute Allowlist
Follow these simple steps to apply for the Pluralis compute allowlist:
Visit the application form: Visit Jobs Ashbyhq form
Complete the application: While the form appears to be a job application, it's actually the allowlist application form (this has been confirmed by the team).
Provide relevant information: Be prepared to share details about your technical background, computing resources, and interest in the project.
Submit and wait: After submitting your application, you'll need to wait for the Pluralis team to review it and respond.
Note: Be thorough in your application. Since this is an allowlist for the initial phase, the team is likely looking for participants who understand the project and can contribute meaningfully.
Announced Rewards
While specific reward details haven't been disclosed, the team has confirmed that contributors will be rewarded for their participation. This could potentially include:
Token rewards (if the project has a token component)
Revenue sharing from the trained models
Early access to the technology
The distribution method and timeline for rewards have not yet been announced.
Connect With Pluralis
Twitter/X: @PluralisHQ
Website: Visit their website for more information about the project
Share this alpha with your community and tag our Twitter/X @leap_wallet
FAQs About Pluralis Protocol Learning
What is Protocol Learning?
Protocol Learning is Pluralis' approach to collaborative AI model training that pools computational resources from multiple participants while ensuring no single entity can obtain the complete model.
How is this different from other AI training methods?
Unlike centralized training by large companies or economically unsustainable open-source initiatives, Protocol Learning aims to create a sustainable ecosystem where contributors are rewarded for their participation without upfront costs.
What kind of computing resources do I need to participate?
Specific requirements haven't been disclosed yet, but you'll likely need a decent GPU setup. The application form will probably ask about your available computing resources.
When will the initial phase begin?
No specific date has been announced yet. Getting on the allowlist now ensures you'll be notified when the program launches.
Is this similar to distributed computing projects like Folding@home?
There are similarities in the distributed nature, but Protocol Learning appears to be developing more sophisticated methods for collaborative model training with economic incentives built in.
What problem is Pluralis trying to solve?
They're working on low-bandwidth, model-parallel training - a technical challenge that would allow efficient distributed AI training without requiring massive data transfers between participants
