Ocean Protocol Combines SMPC with Compute-to-Data for Private AI Training

Ocean Network is rolling out new scaling capabilities for decentralized compute workloads. **Three new features coming soon:** - **Parallel job execution** - Run multiple containerized workloads simultaneously across distributed environments without infrastructure management - **Multi-stage pipelines** - Split complex workloads into smaller stages for improved reliability and easier scaling - **Real-time resource visibility** - View available capacity, runtime limits, and environment details before job submission These additions build on Ocean's existing pay-per-use model, where users authenticate with Web3 wallets and pay only for actual runtime. Jobs run in isolated containers with built-in failure handling and fund escrow protection. Developers can currently test the workflow using the [Ocean VS Code extension](https://open-vsx.org/extension/OceanProtocol/ocean-protocol-vscode-extension), compatible with Cursor, Antigravity, Windsurf, and VS Code editors.

**Lunor AI** has launched the **TripFit Tags** data annotation challenge, running until March 10 with a prize pool of **1,500 USDC**. **How it works:** - Read travel listings and review their details - Categorize each listing by traveler type: Solo, Couple, Family, or Group - Help train smarter travel search systems The challenge offers straightforward tasks that contribute to improving travel recommendation algorithms. Participants label data that will enhance how travel platforms match listings to user preferences. [Learn more about the challenge](https://twitter.com/lunor_ai)

Ocean Protocol has launched Ocean Nodes, a decentralized computing infrastructure designed for AI and machine learning workloads. **Key features:** - Builders can access geographically distributed compute to train, fine-tune, and run models without centralized cloud providers - Ocean C2D (Compute-to-Data) keeps data and algorithms sealed inside containers—compute executes remotely, only outputs are returned - GPU owners can monetize idle hardware by contributing capacity to the network - Jobs run in isolated, containerized environments The infrastructure aims to create a sovereign compute layer for AI that is open and distributed, addressing the growing demand for GPU resources as AI workloads scale. [Learn more about Ocean Nodes](https://docs.oceanprotocol.com/developers/ocean-node)

Ocean Protocol has introduced a **Free Compute feature** to their VS Code extension to address image generation failures during rapid scaling. The new feature allows users to: - Start with small, fixed-seed baselines - Lock their settings for consistency - Save both configurations and outputs - Maintain stable, repeatable runs This approach helps developers **experiment and scale at their own pace** while avoiding common pitfalls that occur when scaling too quickly. Users receive **7,200 seconds of free compute time** to test the feature and get started with their projects. The extension continues Ocean's mission to provide seamless AI development tools that combine compute power, privacy, and algorithms directly within developers' preferred IDE environment.

**CivicLens annotation challenge completed** with 206 contributors analyzing European Parliament speeches for political discourse patterns. **Key achievements:** - Labeled speeches for stance, claims, tone, topic, and ideology - Partnership with @lunor_ai delivered high-quality political data - Results provide insights into political discourse analysis The challenge focused on creating datasets to help AI models detect market-moving political statements more effectively. [Read full details](https://blog.oceanprotocol.com/annotators-hub-civiclens-turning-speeches-into-signals-e27041c3972c)