FEENIXS LABS
Pushing the Boundaries of
Machine Intelligence
Our research team is dedicated to solving fundamental problems in deep learning, distributed systems, and AI safety to build more robust platforms.
Active Experiment
Project Nexus
We are currently training a novel sparse mixture-of-experts model designed to run efficiently on our decentralized global node network. By dynamically routing queries to localized specialist models, Project Nexus aims to cut carbon emissions per inference by 65%.
View Live Training MetricsPublications
Read our peer-reviewed papers on neural optimization and systems architecture.
Browse Library →Open Datasets
Access curated, high-quality datasets used to train our internal models.
View Datasets →Open Problems
View the core challenges our researchers are currently attempting to solve.
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