awesome-golem VS DeML-Golem

If you want to run scientific calculations or similar, I highly recommend Golem. Right now, its best applications are ones that can scale by sharding, to use parallel computations. Think doing 100 similar small jobs on 100 computers instead of 1 large job on 1 computer. One average CPU-month costs $3.17, or you can rent 100 CPU-hours for $0.44. Notable examples are blender_cuda which runs on a GPU, and the entirety of awesome-golem.

Adding the repository to the awesome-golem repository. Doing this makes it possible to scout a neat and organized list of projects, without having to do much digging. There are categories that help go through the list quickly, for those that are looking for something specific.

There are lots of use cases on Golem. Many of which were created by the community. You can keep track of them relatively easily on Awesome Golem (all the applications on that list were created within the last year, for the latest implementation, Yagna).

See everything you can do with Golem: https://github.com/golemfactory/awesome-golem

Golem as a project is larger than it's ever been, there's an awesome list of community created apps and tools, the network has more nodes this year than it has before (stats), there's been over 300k GNT / GLM given out to the community in the GLM Rewards Program, not including bounties and hackathons in the last year (48,000 GLM + 83,180 USDC).

The Golem ecosystem is growing steadily (here’s our Awesome list in case you missed it, recently listed on the overall Awesome repository with over 160k stars!)

There are actually already quite a few things you can do with Golem already before Thorg. It's part of the reason why Awesome Golem, containing all the useful stuffs is already listed on the overall Awesome repo which is the 8th highest starred repo on GitHub.

It's also much easier to build applications on the new network as a potential requestor. We have a lot of community-created apps that people can run and/or learn from. There are also tools that are community-created which never existed around Clay Golem. You can find most of them listed here on Awesome Golem.

Awesome-Golem - for pre-existing applications.

I don't find back the Blockstack link, but here is the github link to federated learning on Golem: https://github.com/anshuman73/DeML-Golem

Hi everyone, this is /u/anshuman73, the author and creator of DeML, the first Machine Learning training implementation on Golem!

KubaM: “If I were to pick one project I'd definitely go with DeML-Golem (https://github.com/anshuman73/DeML-Golem), one of our last hackathon's winners. I think machine learning is a perfect use-case for Golem Network, both in terms of task scalability and free access to the platform (you could train your models for a fraction of the price you'd pay when using a traditional, centralized cloud solution). DeML-Golem shows a proof-of-concept for federated learning on top of Golem and, in my opinion, is very promising. I'm hoping to see it developed further in the near future.”

Question, u/viggith mentioned that machine learning was far down the road because of some hurdles. I saw this winner and wanted to know if new golem can achieve ML and AI quicker than was thought? Decentralized Machine Learning by Anshuman73: utilizes concepts from federated machine learning to combine the sub-steps of models trained on the proof of concept of this app built atop of the Golem Network.