Acknowledgements

We kindly thank (in no particular order)

• Artem Babenko and Vladimir Aliev for helpful discussions and editorial review of the paper,

• Jacob R. Steeves for discussions on RPC frameworks and NAT traversal and peer-to-peer technologies.

• Dmitry Afanasiev for his guidance on networking and communication technologies,

• Lidi Zheng and grpc-aio contributors for their awesome framework and this PR

• Brian Muller for his implementations of kademlia and rpcudp

• Alexander Sherbakov for helpful discussions on PC and server component architecture,

• Yandex School of Data Analysis students, for helping us run first truly collaborative experiments.

• The Neuropark community, for hosting early collaborative training experiments of sahajBERT with hivemind.

• Our early adopters, contributors, and conference reviewers.

Related projects

In this section, we list several organizations and research projects that bring humanity closer to the dream of world-scale deep learning with volunteer computing.

• Hugging Face — an AI community with world-leading NLP research that builds collaborative hub training using hivemind.

• EYDLE — a start-up that works towards distributed deep learning on volunteer hardware using centralized infrastructure.

• BitTensor — a decentralized deep learning ecosystem with incentive mechanism. Each peer trains for its own objective and rewards others for useful features.

• Also building collaborative deep learning? Let us know! hivemind-team <at> hotmail.com