Skip to content

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

Comments

In the past, we funded our work through consulting projects, but looking ahead, we’re going to offer a managed version for enterprises and charge per deployment or federation.

Interesting.

Flower seems to fit well for people who are sensitive about their data and don't want to hand it over to a third party, but this seems to move towards a model where they have to hand that sensitive data over to a third party.

Perhaps that still works for the bulk of users, especially commercial rather than government. It's difficult to pursue both a managed solution and simultaneously maintain an open source offering without one departing from the other.

I didn't read it as a move towards centralizing data, but instead as working with companies to federate over their userbase or between a collection of companies.

Charge per deployment is on-prem? You bring the hardware, they send you the software.

Hey wjnc, You can think of it how you can use GitLab on gitlab.com or deploy it yourself on-prem. The only difference being instead of per user we would charge per deployment. As in case of GitLab you can decide to host it yourself.

AboutSource Built by g1lg1l

Hackerly is an independent reader for Hacker News, built on the public HN API. Not affiliated with Y Combinator.