Academic Collaboration

Pluralis Research https://pluralis.ai/ is pioneering Protocol Learning https://arxiv.org/abs/2412.07890—a fully decentralised way to train and deploy AI models that opens this layer to individuals rather than well resourced corporates. By pooling compute from many participants, incentivising their efforts, and preventing any single party from controlling a model’s full weights, we’re creating a genuinely open, collaborative path to frontier-scale AI. ACADEMIC COLLABORATION Research partnerships at the frontier of decentralized AI. Pluralis actively collaborates with academic researchers to advance the state of Protocol Learning. This is not a job posting, but an invitation for established researchers to explore joint publications and research initiatives focused on low-bandwidth model-parallel training and decentralized AI systems. COLLABORATION OPPORTUNITIES

• Joint Publications: Co-author papers targeting top ML conferences and journals.
• Research Exchanges: Share insights and findings in areas of mutual interest.
• Access to Unique Infrastructure: Leverage our distributed training environment for novel experiments.
• Interdisciplinary Connections: Bridge ML research with distributed systems, economics, and protocol design.
• Potential for Funding: Research grants may be available for promising collaborative projects.
• PhD Sponsorship: We are open to sponsoring PhD's for exceptional students. WHAT WE'RE LOOKING FOR
• Active Researchers: Current faculty, postdocs, or PhD candidates actively publishing in relevant fields.
• Relevant Expertise: Background in distributed ML, model parallelism, federated learning, or related areas.
• Publication Track Record: Demonstrated ability to publish in peer-reviewed venues.
• Collaborative Mindset: Interest in open exchange of ideas and joint problem-solving.
• Alignment with Mission: Enthusiasm for democratizing access to frontier AI capabilities. APPLICATION PROCESS
• Complete this brief form describing your research interests and relevant experience
• Include links to representative publications or ongoing work
• Our research team will review submissions and reach out to discuss potential collaborations
• No formal commitment is required to apply—this is simply an invitation to begin a conversation Backed by Union Square Ventures https://www.usv.com/and other tier-1 investors, we’re a world-class, deeply technical team of ML researchers. Pluralis is unapologetically ideological. We view the world as a better place if we are able to implement what we are attempting, and Protocol Learning as the only plausible approach to preventing a handful of massive corporations monopolising model development, access and release, and achieving massive economic capture. If this resonates, please get in touch.

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