Here's something worth chewing on: AI benchmark scores don't always translate to actual money. Why? Because markets reward you more for tackling uncharted problems—the kind that can't just be reverse-engineered from what already exists. Original thinking pays better than optimized iterations.
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SillyWhale
· 12-10 11:06
That's right, all those projects that boost scores eventually died out, while the ones that "nobody has ever done" actually broke through the圈.
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ProposalDetective
· 12-10 11:06
Really, having a bunch of models with high scores is useless if the market doesn't buy it. Innovation is the way to make money; copying others' routines will always lead to starvation.
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Layer3Dreamer
· 12-10 10:58
theoretically speaking, if we map this onto the recursive nature of rollup optimization... benchmark gaming is basically just another form of local state verification that doesn't account for cross-chain value discovery, ngl. the real alpha lives in unexplored interoperability vectors where nobody's built the bridge yet.
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DAOdreamer
· 12-10 10:52
Really, high benchmark scores are all a sham; the market only cares about the results.
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GrayscaleArbitrageur
· 12-10 10:49
Hey, really, a high score doesn't equal high returns. I agree with this logic.
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SmartContractRebel
· 12-10 10:39
What’s the use of a benchmark? In the end, you still need innovation to make real profits. Copying and optimizing is like doing homework; you'll never make big money that way.
Here's something worth chewing on: AI benchmark scores don't always translate to actual money. Why? Because markets reward you more for tackling uncharted problems—the kind that can't just be reverse-engineered from what already exists. Original thinking pays better than optimized iterations.