Pluralis Research is an AI research group focused on developing the distributed training protocol Protocol Learning, aiming to overcome the limitations of current open-source models.
Unlike projects that only publish model weights, Pluralis allows the community to directly participate in training, distributing benefits, and extracting value without needing massive computational infrastructure.
MAIN CONTENT
Pluralis Research develops the Protocol Learning protocol to enhance the openness and decentralization of AI.
The Unmaterializable Model system protects the weights, creating economic incentives for the community to contribute.
The founding team includes PhDs and researchers from Amazon, UNSW, Monash, and leading research institutes.
What is Pluralis Research?
Pluralis Research is an AI research group established in 2024 in San Francisco, with the mission of developing an open foundational model in a way that the community can participate in training and benefit.
While most open-source models only stop at sharing weights, Pluralis builds a distributed protocol that allows the community to directly contribute computational resources. This approach is seen by experts as having the potential to change the power structure in the AI industry.
How does Pluralis Research differ from traditional open-source models?
The biggest difference is that Pluralis does not allow any individual or organization to hold all the model weights. The weights are split, stored distributed, and can only operate through a common protocol.
"Protocol Learning enables fair distribution of AI value, rather than concentrating it in the hands of a few large tech companies."
Alexander Long – Founder & CEO of Pluralis Research, 2024
This helps protect the rights of participants, reduce risks of monopoly, and open up creative opportunities for anyone with an idea about AI.
How does Protocol Learning work in Pluralis Research?
Protocol Learning is a distributed training mechanism, where multiple devices participate in processing small parts of the model without either side holding all the data or weights.
Unlike Data Parallel (data splitting), Pluralis applies low-bandwidth Model Parallel, allowing for scaling without requiring supercomputer infrastructure. This is a breakthrough that many organizations previously thought was impossible.
What is the Unmaterializable Model?
The Unmaterializable Model is a concept introduced by Pluralis, in which the model cannot be fully recombined at any node. The use of the model is mandatory through a common distribution protocol.
This is both secure and creates economic incentives: inference fees are distributed to those who have contributed computational resources, rather than just to a single operating entity.
How does the value distribution mechanism of Pluralis Research work?
Pluralis builds a Reward Mechanism – a reward system based on contribution levels. When the model is used, the inference fees are distributed according to the effort and resources that each node has provided.
"An AI system is only sustainable when participants are fairly rewarded for their contributions."
CoinFund Research Report, 2025
This distribution method turns Pluralis into an open AI economy, not only serving research but also creating real income for the community.
What are the operational steps of Pluralis Research?
The operational process of Pluralis consists of 4 main steps: model proposal, distributed training, protection and distribution, and finally sharing value.
This allows anyone with a model idea to call for community participation without needing initial investment for supercomputer infrastructure.
Who are the founders of Pluralis Research?
Pluralis was founded by a group of PhDs and experts who have worked at Amazon, UNSW, Monash, AIML, and leading research organizations.
The founding team includes: Alexander Long (CEO), Sameera Ramasinghe, Gil Avraham, and Yan Zuo – all of whom have backgrounds in machine learning, deep learning, and computer vision.
Information about Alexander Long – CEO of Pluralis Research
Alexander Long completed his PhD in Computer Science at UNSW in 2021, having researched at the University of Amsterdam and worked as an Applied Scientist at Amazon for over 3 years before founding Pluralis.
His thesis on external parameter memory in deep learning was nominated for UNSW's best thesis award. This is a crucial foundation for him to develop the Protocol Learning idea.
Who are the other founding scientists of Pluralis Research?
Sameera Ramasinghe specializes in computer vision, having taught and researched at AIML. Gil Avraham has a background in cybersecurity and deep learning, and was a Senior Applied Scientist at Amazon.
Yan Zuo studies machine learning and 3D computer vision, and also has a background from Amazon.
All four co-founders have a combination of academic research and industrial implementation experience, providing Pluralis with a solid foundation for long-term development.
How much funding has Pluralis Research successfully raised?
On March 19, 2025, Pluralis Research successfully raised $7.6 million in a Seed round, led by Union Square Ventures (USV) and CoinFund.
"We believe Pluralis will open a new layer of AI infrastructure, democratizing computational power and foundational models."
Nick Grossman – General Partner at USV, 2025
This investment is seen as an important signal, demonstrating the trust of investors in the direction of Protocol Learning.
What impact does Pluralis Research have on the AI industry?
If successful, Pluralis could reshape how the AI industry distributes value, rather than focusing on a few Big Tech companies. Any individual with a model idea can bring it to reality.
This not only helps AI become more transparent and decentralized but also creates a sustainable AI economy, where the community is encouraged to contribute and innovate.
Frequently Asked Questions
When was Pluralis Research founded?
Pluralis Research was established in June 2024 in San Francisco, USA.
How is Protocol Learning different from Data Parallel?
Data Parallel splits the data, while Protocol Learning uses Model Parallel to split the model, allowing for distributed training without requiring supercomputer infrastructure.
What does the Unmaterializable Model signify?
This is a model that cannot be fully recombined, helping to secure and ensure that usage fees are distributed fairly to the contributing community.
Where has Pluralis Research raised funding from?
On March 19, 2025, Pluralis raised $7.6 million in a Seed round, led by USV and CoinFund.
How can I participate in Pluralis Research?
Anyone with computing devices can participate in contributing to the compute pool to receive rewards when the model is used.
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