The quickest way to run your first compute job is to use the Ocean Network dashboard: select the resources you need, then push them to Ocean Orchestrator (you’ll be prompted to install it if you haven’t). Ocean Orchestrator works in VS Code, Cursor, Antigravity, and Windsurf. If you prefer CLI, you can use ocean-cli to submit the job and pull results when processing is complete.

Yes. You can run AI jobs in VS Code, Cursor, Antigravity, and Windsurf using the Ocean Orchestrator extension, with job orchestration handled behind the scenes, and outputs saved to your chosen results folder.

You can run containerized compute jobs like embeddings, model inference jobs, data cleanup, batch processing, and fine-tune model workloads that finish within the job window and produce outputs you can download.

Currently, we are providing templates for Python and JavaScript in the extension workflow, but you can also add your custom container, allowing you to use any programming language you prefer

Ocean Network is a decentralized, peer-to-peer (P2P) compute network for pay-per-use compute jobs that turns idle or underutilized GPUs into usable distributed compute resources. It lets you choose a preferred Ocean Node with the resources you need, submit a containerized job, and get results back without managing servers or infrastructure

Compute is the resource you spend in order to get your code to run, like model inference, embeddings, fine tune model runs, and data processing. Decentralized compute means that resource comes from many independent machines in a P2P compute network, so your job can run on distributed GPU or CPU capacity and return outputs. With Ocean Network, you select the Ocean Node and resources you want, submit the job, and get results back without managing servers, using a serverless style workflow across that distributed capacity.