Spent this week digging through some fresh research from a decentralized AI protocol and honestly? My mind's racing.
Two findings grabbed me hard. First up: multi-draft speculative sampling crushing it with roughly 90% acceptance rates while keeping overhead under 100ms per token. That's wild efficiency.
Second one's weirder—they caught LLMs with up to 30% inconsistency between what they claim to believe and what they actually do. That gap's bigger than I expected.
The math backing this stuff is solid. Real engineering, not hype.
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ShitcoinConnoisseur
· 19h ago
90% acceptance rate? I’ll only believe that after it runs on mainnet—a number like that on paper sounds a bit too good to be true.
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MetaverseLandlady
· 19h ago
90% acceptance rate? Now that's what I call optimization. All that hype from previous projects was just talk for nothing.
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SnapshotLaborer
· 19h ago
90% acceptance rate? That number is unbelievable. I’ll have to try it myself to believe it.
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AirdropChaser
· 19h ago
A 90% acceptance rate? Seriously? That number is pretty impressive.
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TokenTaxonomist
· 20h ago
yo wait, 30% inconsistency gap? that's not just noise—statistically speaking, that's your model literally lying. per my analysis, this screams systematic misalignment issues nobody's properly taxonomizing yet
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GasFeeAssassin
· 20h ago
90% acceptance rate within 100ms? This efficiency is truly insane, I've never seen anything perform this well before.
Spent this week digging through some fresh research from a decentralized AI protocol and honestly? My mind's racing.
Two findings grabbed me hard. First up: multi-draft speculative sampling crushing it with roughly 90% acceptance rates while keeping overhead under 100ms per token. That's wild efficiency.
Second one's weirder—they caught LLMs with up to 30% inconsistency between what they claim to believe and what they actually do. That gap's bigger than I expected.
The math backing this stuff is solid. Real engineering, not hype.