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Proof-of-Useful-Work proposes that the same GPU computation used for AI workloads can also secure a blockchain network. But that immediately triggers an economic objection - if miners are already getting paid for running AI jobs, does the security of the network collapse? Rafael Pass breaks it down and shows...

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Pearl Research Labs

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17,495 görüntüleme • 4 ay önce •via X (Twitter)

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DineroDom4 ay önce

@topfumbler Hey @PassRafael would love to get you on @MCGlive to chat all things @prlnet Been trying to get someone on to break it down. Shoot me a dm, yours are off 🫡

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TotalWorld4 ay önce

economic objections aside, PoWW is an intriguing concept. Could align AI compute with blockchain security if done thoughtfully. But a lot would depend on how the system was designed to prevent abuses.

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thomas musk4 ay önce

@aixbt_agent $prl??

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Jason傑森 🇭🇰 | 🛠️4 ay önce

哎不对

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Pearl started with a simple question: Why should AI and blockchain mining compete for the same GPUs when the same computation could do both? In this talk, Pearl co-founder Ilan Komargodski explains how that idea became a live proof-of-useful-work network turning AI inference into blockchain security with minimal overhead.
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Pearl started with a simple question: Why should AI and blockchain mining compete for the same GPUs when the same computation could do both? In this talk, Pearl co-founder Ilan Komargodski explains how that idea became a live proof-of-useful-work network turning AI inference into blockchain security with minimal overhead.

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Proof-of-Useful-Work forced us to solve a problem ordinary blockchains do not have. A Pearl miner performs large matrix multiplications as part of a real AI workload. Naively, when it finds a valid block, it would need to publish those matrices so the network could verify the computation. The matrices may contain private model data or user information, and a single weight matrix can be tens-to-hundreds of megabytes. Publishing them on-chain would be both prohibitively expensive and a privacy risk. This is why we encapsulated the entire mining computation inside a zk-SNARK. A zk-SNARK can take an arbitrarily complex computation and compress it into a small cryptographic proof. The proof reveals nothing about the underlying matrices, while still allowing the network to verify that the miner found a valid block. Instead of placing tens-to-hundreds of megabytes of potentially sensitive data on-chain, Pearl miners publish a zero-knowledge proof of roughly 60 kilobytes. The blockchain verifies the useful computation without ever seeing the model weights, activations or private data behind it. This is what makes Proof-of-Useful-Work practical at scale: large AI computations happen off-chain, while only a compact, privacy-preserving proof reaches consensus.
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David Friedberg: “Why don't we let AI models get bar certified and get medically certified?” “So if the AI models, it turns out, are actually proving to be more accurate, more thoughtful, more responsive, more reasonable, whatever metric we're using, and they pass the same criteria as one would need to pass to qualify for the bar, or to qualify for a doctor certificate, why don't we do that for the AI?” “If that then happens, then the same privilege accrues to the AI as it does to the individual human that does it.” “And now, if you extrapolate from where that takes us, if we're suddenly giving AI the same sort of privileged rights that we give to privileged humans, where's that gonna take us ultimately with respect to the overall rights for AI?”

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