There was a product I personally liked called graphistry but that isn’t free persay, but its founder is brilliant in this space @lmeyerov

looks like they've introduced some differential privacy wrappers, the changelog points to that: https://github.com/adap/flower/blob/94a1f942abfce5dff4e9aff2...

Yes, we have developed modular and efficient secure aggregation and differential privacy solutions that can help people dial in the amount of protection they need. We have documented an early version of the secure aggregation here: https://flower.dev/docs/secagg.html Documentation and updates on both methods will be released soon.

I hate to ask a product comparison question, but why would I use this versus other projects like PySyft.

Thanks for the question, very natural to ask. We are also fans of PySft. It offers support for a very wide range of privacy enhancing machine learning tools. But where Flower and PySft differ is in focus. Federated learning is difficult and requires many technical moving parts all working together (e.g., secure aggregation, differential privacy, scalable simulation, device deployments, integration with conventional ML frameworks etc.). All of these need to tightly integrated, and in a manner that performs federated learning efficiently. This is where Flower currently excels. It offers comprehensive, extensible and, most important, easy to use construction of federations that need these different parts together. We believe it offers the best user experience for federated learning currently out there. We hope in the future many tool suites that offer private machine learning (like PySft and others) will actually adopt Flower components so we can all work better together.

Can confirm that PySyft is currently in the process of integrating with Flower. Best of both worlds.

Indeed - looking forward to this

I appreciate you taking the time to break this down, I’ve spent a decent chunk of time having to roll my own stuff so when pygrid/pysyft came along it was just easier. I will say the flower components look interesting and I’ll give it a shot

Thanks for adding this here! We added these DP wrappers, and we're working on something similar for Secure Aggregation, but I must admit that we have to document them better to make using them easier for everyone

Another interesting project to checkout is klange’s toaruos https://github.com/klange/toaruos

At first I read this as "tortuous", then "to aru" (toh ahru). So, despite not having watched the show, I'm now thinking of railguns.

I had to chuckle given the detail of the article such as it is.

It’s not the site we wanted but the one we needed but never knew.

Holy shit that copay is high, I had Kaiser too at one point and mine came out to $200ish a month with $20 copays. I know stuff varies but Kaiser felt like highway robbery

~$350/month, which to me has been useless so far. Generally costs about 20k USD a year in the US split between employers and employees

I'm curious if using three.js + WASM acceleration might help with this

@jart, just wanted to say thanks for both APE and cosmopolitan, those projects have made my life infinitely easier as well as giving me a lot of my time back not having to figure out windows executable minutia. It's a no brainer for me to create either a WASM module or an APE to get the job done.

And also tysm @jart for derasterize https://github.com/csdvrx/derasterize, which was a great basis to work on, and helped me make sixel-tmux https://github.com/csdvrx/sixel-tmux

We achieved textmode supremacy, and jart achieved binary-portability supremacy.

There seems to be a pattern here :)

If you get the opportunity, there is a Bartholdi museum in a small town on the French German border called Colmar that was originally his home. It’s interesting the evolution of the artist over the decades leading up to the Statue of Liberty