Edge Computing 🤝 Federated Learning The next AI breakthrough lies in unlocking private data. By expanding training from public to private data, FLock enables AI models to specialise, delivering deeper insights and continuous innovation. Introducing the FLock FL Alliance.

2/ The Problem AI models today rely on public data, limiting their adaptability in specialised fields like healthcare and finance. The next wave of AI will emerge via innovations in model training and AI agents. Leveraging the vast private data generated daily could enhance model creativity, but ensuring data privacy remains a key challenge.

3/ The Solution: Collaborative LLM Training on Edge Device Clusters FLock combines Edge Computing with Federated Learning, shifting model training to user-end devices (e.g., phones, laptops). This means: + Private data stays local. + Devices share encrypted parameters, not raw data, ensuring privacy. + Distributed computing reduces latency and improves efficiency.

4/ FLock turns private data into a game-changer for AI where engineers can securely train richer, more precise models as devices encrypt and process data locally. On the other side, users maintain full privacy and are rewarded for their contributions to the models.

5/ Our vision is clear: to unlock the potential of private data while safeguarding user privacy. By combining Edge Computing and Federated Learning, we are building a DeAI future that is private, secure, and innovative. Your model, your AI.

OpenAI is betting on a little-known startup to stay ahead of Elon Musk in the supercomputer race.

AI's next frontier: Private data! FLock's Federated Learning Alliance unlocks deeper insights.

Great vid!

Glad you liked it Richard!

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Flock got everything we need to unveil a new computing world.