AIOZ Network

Excited to unveil the AIOZ Network Vision Paper V2! Dive into our vision for a unified DePIN layer powering: → Decentralized storage (AIOZ Storage) → Content pinning/caching (AIOZ Pin) → Streaming & delivery (AIOZ Stream) → AI inference orchestration (AIOZ AI) An end-to-end DePIN stack with flexible monetization and stronger developer enablement. Read now & build the people-powered internet with us! Link: aioz.network/aioz-vision-v2…

Join the challenges: aiozai.network/challenges

Explore AIOZ Stream: aiozstream.network/overview

Streaming performance is shaped layer by layer. AIOZ Stream aligns workflow design across the media pipeline, from content entry to playback. What this supports: → Ingest across multiple media inputs → Preparation for packaging, segmentation, and adaptive delivery → Storage and delivery powered by DePIN and AI Stage-level optimization improves reliability, quality consistency, and delivery efficiency. Design your pipeline with AIOZ Stream, from ingest to delivery.

Discover AIOZ Storage: aiozstorage.network

From raw datasets to trained model assets, storage underpins AI workflows. AIOZ Storage supports AI pipelines with S3-compatible object storage for growing data demands. What this enables: → Scalable handling of datasets and models → Distributed durability with no single point of failure → Fast data access for training and inference → Cost-efficient storage for data-intensive workloads Better storage architecture reduces friction from data to deployment. Explore how AIOZ Storage fits your AI workflows.

Join the challenge: aiozai.network/challenges/mel…

Not sure where to start in the Melanoma Skin Cancer Classification Challenge? Pro tip: Before tuning your model, understand the baseline execution path end to end. → Open the run file, then find do_ai_task() → Place trained weights in the models folder → Use the demo file as your feedback loop → Don’t edit the init or submission files Submit once, then iterate with confidence.

Streaming demand now goes beyond the upload–store–deliver model. AIOZ Stream is designed for creators, viewers, and developers across a broader media workflow. What this supports: → Video and audio publishing across creator-led and multi-format media → DePIN-powered infrastructure for adaptability and reliability → Architecture ready for evolving monetization logic Pipeline design now shapes product outcomes across distribution, growth, and experience quality. Explore how AIOZ Stream fits your media workflows.

Join the challenge: aiozai.network/challenges/mel…

Explore the LightRAG on AIOZ AI: aiozai.network/models/8e01a1d…

Join the Challenge: aiozai.network/challenges/mel…

Join the challenge: aiozai.network/challenges/mel…

Early detection changes everything in melanoma outcomes. The Melanoma Skin Cancer Classification Challenge is now LIVE on AIOZ AI. What you’ll practice: → Binary classification on dermatoscopic images (benign vs malignant) → Preprocessing and augmentation for medical imaging data → Transfer learning for small, high-impact datasets This is where model accuracy meets real clinical relevance. Ready to build on a real-world vision task? Join anytime. No final deadline.

Download AIOZ DePIN CLI v1.2.6: aioz.network/aioz-depin

AIOZ DePIN CLI provides operators with a direct path to run DePIN services through scriptable, production-ready workflows. What’s included in CLI v1.2.6: → Native AI compute integrated into the DePIN runtime → Unified visibility across storage, delivery, transcoding, and AI → Explicit storage controls for predictable resource usage → Built-in health checks with automatic recovery → Experimental auto-update for long-running environments Get started with AIOZ DePIN CLI and run your first AI-enabled DePIN workflow today.