I'm very familiar with FL frameworks. I chose Flower after having spent a lot of time benchmarking many of them. FedML wasn't able to carry on the easiest workloads I tried, like the baseline of the Shakespeare dataset. The simulator you have was the slowest compared to the other frameworks I tried. Your platform doesn't give developers like me what they want. Flower was the best to use since day one.

As a founder of an FL startup, I strongly advise against using FedML as it is one of the worst frameworks in terms of scalability. Regrettably, the FedML team has also a poor reputation due to their toxicity and suspicious behavior. If you value the trustworthiness of your product, I suggest avoiding FedML at all costs.

LOL, starting FL wars, are we? I never tested FedML in production but it was cool for simple experiments. I concur with what you are saying though about their devs. The CTO is super sus.

OMG, hard to believe that this is from Flower founder's words. I am just a federated learning user and told the truth to the audience here. I have followed the FL community for more than 2 years, and I clearly feel that Flower has been copying and following FedML's product plan without any originality at all. These nonfactual attacks further makes me distrust on Flower team. You are ruining the reputation of YC. You need to gain the trust of users like FedML team, not attack their reputation. Please stop doing so.

FedML is definitely much simpler and more powerful in both research and production. In terms of scalability, I like the benchmarking results in this paper (https://arxiv.org/abs/2303.01778); it shows that FedML is much more scalable. I also tried it myself, it's faster and more scalable. In terms of "research to production", I don't see Flower supporting any MLOps functionalities. Is Flower trying to copy FedML again in this direction?

*just a federated learning user* flashing a two-week old academic junk from the FedML team. Sus af. No f'ing way I am using a privacy product from the glorious land that gave us Tiktok and mass government surveillance.

Because that one is an important work for scalability, so I followed it closely.

I will stop here due to your disrespectful words. Good luck.

I'm not sure what pre-existing conflict is breaking out in this subthread between accounts created for the purpose, but would all of you please stop?

One of the creators of Flower here - I can only say that the team behind Flower appreciates the contributions of FedML to the field of federated learning. Their work helps to make federated learning more widely known, and they published significant advances in making federated learning more robust and scalable.

In fact, we are in the process of implementing LightSecAgg, and we'd welcome their feedback once we have a working version.