Paragon AI is a groundbreaking framework that democratizes advanced neural network training through distributed micro-network surgery, type-generic architectures, and WebGPU acceleration.
We believe artificial intelligence should be accessible, efficient, and distributed. Too many brilliant minds are held back by expensive cloud computing costs and centralized AI infrastructure.
Paragon AI breaks down these barriers by enabling distributed neural network training across everyday devices - phones, laptops, and edge computers - while maintaining state-of-the-art performance through revolutionary micro-network surgery techniques.
Cloud GPU training can cost $100k+/month for enterprise models
Traditional training takes days or weeks for architectural experiments
AI development concentrated in big tech companies with massive resources
Billions of devices sit idle while AI researchers wait for compute
Extract, modify, and reintegrate neural network segments without losing model integrity. Our breakthrough technique allows surgical modification of specific network layers while preserving overall performance.
One codebase supports Float32, Float64, Int32, and Uint32 networks. From GPU-optimized floating-point to memory-efficient integer networks for edge devices.
Accuracy Deviation Heatmap Distribution scoring provides precise model evaluation beyond traditional metrics. Advanced performance assessment for optimization decisions.
Leverage idle computing power across phones, laptops, and edge devices. Automatic load balancing and fault tolerance enable planetary-scale neural networks.
Native GPU acceleration using modern WebGPU standards. Lightning-fast training and inference across browsers and devices without traditional GPU computing barriers.
Networks that evolve automatically based on performance metrics and data complexity. Self-improving architectures that adapt to new challenges without manual intervention.
Paragon captures the state of neural network layers at strategic checkpoints, creating snapshots that preserve learned representations.
Extracted network segments are surgically modified - adding layers, changing activations, or optimizing architectures - while maintaining compatibility with the main network.
Multiple devices simultaneously experiment with different improvements, creating a parallel search space for optimal architectures.
ADHD scoring system evaluates each improvement candidate, measuring not just accuracy but deviation patterns and confidence distributions.
The best improvements are surgically reattached to the main network, evolving the architecture while preserving existing knowledge.
Cost Reduction
vs Traditional Cloud Training
Faster Iteration
Architecture Experiments
Scalability
Every Device is a Worker
Open Source
Apache 2.0 Licensed
Democratizing AI development for researchers, startups, and enterprises worldwide
Universities and research labs with limited compute budgets can now compete with well-funded tech giants. Distribute training across student devices and campus infrastructure.
Early-stage companies can build sophisticated AI products without massive infrastructure investments. Scale intelligently using distributed resources.
Large organizations can leverage existing device infrastructure for AI training, reducing cloud costs while improving model performance through distributed optimization.
Mobile and IoT developers can create sophisticated on-device AI using memory-efficient integer networks and optimized architectures.
Founder & Lead Developer
Passionate about democratizing AI and building the future of distributed intelligence. Believes every device should contribute to humanity's AI advancement.
Open Source Contributors
Paragon is built by and for the global AI community. Researchers, developers, and enthusiasts from around the world contribute to advancing distributed AI.
Future Contributor
We're always looking for passionate developers, researchers, and AI enthusiasts to join the mission of democratizing artificial intelligence.
Join thousands of developers, researchers, and innovators building the future of distributed artificial intelligence.
Apache 2.0 Licensed • Free Forever • Built by the Community