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Comment by amitport | Hacker News Reader

The blog post, demo, and website are incredibly uninformative (maybe informative, but not on own product's details). Eventually, pressing on "getting started" goes to a sign up for updates page.

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The first link is the corporate website, it may not include all the product details you expected, sorry about that. You should get a lot more details on how it works if you try the tutorial and play with it yourself. This is at the bottom of the post, hopefully it satisfies your curiosity but happy to answer outstanding questions here of course.

Is this a productized Duet[1]? Are you using it under the hood?

(As far as I'm concerned, if the answer is yes to both, this has much potential. I'm just trying to figure out what I'm looking at)

Thank you!

[1]: https://blog.openmined.org/duet-demo-how-to-do-data-science-...

Yes, there are many parallels with Duets we can look at Sarus as a productized version of it.

There are some differences though: - we designed for the trusted curator model where Duet is mostly for federated learning tasks in mind - the privacy policies are based on principles (such as: "DP-outputs with epsilon < 2 can be shared", "DP-synthetic data can be shared", or "weights of ML models can be shared"), then the gateway applies the principles to any query, whether it is a SQL query, an ML model or else. In Duet, it's all about manual validation of given queries.

The PySyft project is well-documented and researched if you want to learn about the technology.

Yes, this is a very rich resource. Thx

Is PySyft used under the hood?

No, we do not. Pysyft was mostly first designed to do federated learning. Sarus targets organizations that have their data in one central repository in a trusted curator model. It lets external data practitioners query that data with all sorts of data jobs (not just ML, but also SQL analysis, and spark soon).

side question: Is federated learning used in production? if not why?

No, we don't do federated learning at Sarus today. We operate in the trusted curator model: a party has a centralized database and lets external practitioner leverage it. This is the most common setup in the industry (think hospitals, health insurance companies, banks, streaming services...).

That being said, Sarus can be used to protect one node of a federated learning network. For instance each hospital could have a Sarus instance. The data scientist would need to take care of the orchestration of the nodes themselves but the Sarus API would make their life easy to interact with each data source, especially if all the sources are not identical.

I'm very familiar with pysyft and tensorflow federated (and Duet which may be the open source basis for this kind of product). I have much interest on the topic and that's why I was seriously scanning the website and tried to understand what the product is exactly. I failed.

It looks like someone asked an AI model to generate a website for the next YC company

this page specifically https://www.sarus.tech/solutions just screams "UX is an afterthought"

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