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Comment on Launch HN: Flower (YC W23) – Train AI models on distributed or sensitive dataparent

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Thanks, we're excited too!

Flower tries to automate this as much as it can. In cases where multiple organizations are involved, the workload can run in a fully automated manner if that's fine for all organizations. If a review step is required, that can be integrated (either on the client side or on the server side) - the availability of reviewers will then become the bottleneck for end-to-end latency.

In the long run, we will evolve the permissioning system to allow workloads to be automatically executed if they fall within pre-approved boundaries, or require manual review if they don't. Pre-approved boundaries could, for example, be used to configure a particular combination of models and hyperparemter ranges that are ok to run without additional (manual) approvals.

Awesome! Makes sense. I think the challenge is going to be coordinating with the various orchestration systems -- timeouts, etc.. Excited to see how you pull it off!

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