The future of AI isn't about building monolithic systems in data centers. It's about training models centrally, then adapting them locally, and ultimately running inference at the edge. This distributed approach isn't just more efficient—it's a competitive advantage. When companies control their own data and compute infrastructure, they gain genuine digital sovereignty. Competitiveness and sovereignty reinforce each other in this model: the more distributed your systems are, the harder you are to disrupt. That's the real paradigm shift happening now.

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LiquidationWatchervip
· 8h ago
Decentralized training inference sounds good, but the real challenge is who will ensure data security.
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BTCBeliefStationvip
· 8h ago
Decentralized training + local adaptation + edge inference, this approach is truly brilliant. Holding the data is like holding the lifeline.
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OldLeekNewSicklevip
· 8h ago
It sounds like slicing up the big model's cake to share with everyone, essentially the same "decentralization" marketing tactic. Edge computing inference indeed saves costs, but who can truly control their own infrastructure? Most companies still have to rely on cloud providers' frameworks, just with a different name.
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SandwichHuntervip
· 8h ago
Wake up, wake up. This is what Web3 should be doing. I've already talked about data ownership rights.
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