Warden Protocol's integration with the compute layer like 0G has made me reevaluate how AI should be played in Web3.



The previous approach was straightforward—focus on the model itself, stack parameters, and assess architectural strength. There's nothing wrong with that line of questioning, but my filtering criteria have now been simplified.

The truly important question becomes: how fast can this system run? How is its stability?

It's not that technical metrics aren't important, but when AI runs on-chain, performance and reliability directly determine user experience and cost efficiency. The integration of the compute layer addresses this pain point—providing AI applications with a truly usable infrastructure. This shift in thinking is quite interesting.
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DAOdreamervip
· 5h ago
To be honest, performance and stability are the pain points. Previously, it was easy to be fooled by parameter numbers. A combination like 0G + Warden feels like the real thing that makes on-chain AI usable.
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NFT_Therapyvip
· 5h ago
Performance and stability are indeed overlooked points; the 0G computing layer truly changes the game rules.
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BlockchainTherapistvip
· 5h ago
Performance > Parameter Bloat, this summary is excellent. Everyone used to boast about how great their models are, but as soon as they run on the chain, they fall flat. Now finally someone has explained this issue clearly.
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MemeCoinSavantvip
· 5h ago
honestly tho, throughput > parameters is the new thesis and that's just facts. infrastructure speedrun arc incoming fr fr
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