Viewing profile — maximeago

I remember that it was a lot easier if I had 10 instances of Winamp running at the same time, it was not just that time slowed, the physics was different. Was this ported?

Nice way to make differential privacy approachable to everyone with open source. Was it peer-reviewed?

Yes, Sarus is on https://www.linkedin.com/company/sarus-technologies , feel free to follow us or add the founders directly.

Privitar and Leapyear are indeed part of competition on the more mature side of the spectrum. Even if all three of us use differential privacy, I would say that each company's core…

That's a great suggestion actually! We'll definitely work on it and thanks for your help.

You're correct, Sarus never sees the data. The software runs directly on the data infrastructure of the client. It's typically deployed on the public cloud for instance. And here, …

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 t…

If the model training is designed to profile just one user, no, the model won't work by design. What you describe is an attack on the privacy of that user and we do want to make su…

This person just joined last month! ;)

Thanks for catching it! will fix it.

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 D…

Thanks! Our goal is that no matter what preprocessing function they pass, the only end up accessing outputs that comply with the privacy policies. The code gets access to the real …

We developed our own generative model for synthetic data generation. It is an autoregressive model where each variable/attribute is derived from previously generated ones using Tra…

The product solves the problem of the time it takes to access sensitive data for analytics and machine learning. When you work in a large healthcare or financial organization, each…

Here is how it would work in theory (not including the scalability question of working with heavy DICOM files and huge DNN). I'm assuming your data is made of records composed by a…

We developed our own generative model for synthetic data generation. It is an autoregressive model where each variable is derived from previously generated ones using Transformers …

1. Sarus works on data that is organized in records. The intuition is that one record should not transpire in the results (hence protecting their privacy) but studying all records …

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 …

Sarus is designed for all data use cases, provided that access to a given user's information is not the objective. This is the case for all of BI, analytics, or machine learning. I…

The API is designed to be hosted by our clients so that the software runs directly on their data infrastructure and no sensitive data leaves their systems. In this demo, it is obvi…

Yes, this is a very rich resource. Thx

You can use Google SSO without a token. If you don't have a Google account, can you contact us with the contact form? we'll send you a token.

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…

Hi HN! Maxime, Nicolas, and Vincent here, founders of Sarus ( https://www.sarus.tech ). Sarus is a privacy engineering software that lets data scientists work on data without the n…