Joined January 2021
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Jan 26
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.…
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The License Plate Recognition Challenge is now live on AIOZ AI.
Build a detect-then-read pipeline that locates license plates in vehicle images and recognizes the characters.
What you can practice:
→ Python-based computer vision workflows
→ Deep learning for image understanding
→ Object detection for license plate localization
→ Optical Character Recognition (OCR) for plate text
Total prize pool: 4,500 AIOZ tokens
Registration ends: June 28, 2026 ET
Join the challenge now.
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Jun 10
AIOZ AI Major Update: API Access Is Rolling Out
The models you've been running in Playground can now run in your code.
What we shipped:
→ API Keys for solo and team access
→ REST API with one endpoint per model
→ Official SDKs across Python, Node.js, and Go
Now you can:
→ Run inference in batches
→ Wire models into backends
→ Chain AI pipelines
A model you can click is a demo. A model you can call is a building block.
Create a key, make your first call, and start building.
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Jun 9
AIOZ Storage supports media workflows with S3-compatible object storage for fast access, sharing, and file management.
What this enables:
→ Metadata-rich storage for media and application assets
→ Fast access to large files through AIOZ DePIN
→ Cost-efficient storage for growing workloads
From media libraries to large-scale content delivery, storage architecture shapes speed, accessibility, and workflow efficiency.
Explore how AIOZ Storage fits into your media workflows.
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Jun 8
Started the Spaceship Titanic Prediction Challenge yet?
Pro Tip: Don’t drop every row with missing values.
Missing values are scattered across the dataset.
Dropping incomplete rows may remove roughly a quarter of your training data.
Use a clear strategy:
→ Median for Age and amenity spending
→ Unknown for categories
→ Test False vs Unknown for CryoSleep and VIP
Handle the gaps. Train with consistency.
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Jun 4
AIOZ Storage brings more than storage to your workflows.
What this supports:
→ Static Website Hosting for docs, landing pages, and SPAs
→ Custom Domains for branded websites
→ Automatic MIME Type Detection
→ Access Grants for scalable access control
AIOZ Storage keeps application workflows familiar and scalable.
Build your next workflow with AIOZ Storage.
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Jun 3
AIOZ Stream brings peer-to-peer media delivery through distributed contribution across AIOZ DePIN.
What this supports:
→ DePIN-powered delivery with flexible capacity
→ Sharding and redundancy for strong continuity
→ Integration across AIOZ Storage, Pin, and AI
Delivery architecture shapes resilience, scaling, and cost structure across the media pipeline.
Discover how AIOZ Stream fits your media stack.
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Jun 2
Started the Spaceship Titanic Prediction Challenge on AIOZ AI?
Pro tip: Parse compound columns before tuning your model.
Start with these two columns:
→ Split PassengerId to identify travel groups and passenger order
→ Split Cabin to capture deck, cabin slot, and side
These raw strings hide useful signals.
Download the data. Split first. Then train smarter.
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