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Claims - Subnet 111
@DeSciClaims
Turning 300M scientific papers into a validated claim-evidence graph, so AI can reason over what science actually shows. Built on Bittensor.
参加 June 2026
106 フォロー中    625 ファン
Chatting with Grant about what we're building was super fun. Thanks for having us on the pod! @VenturaLabs
Ep. 99 - Philipp Koellinger & Christian Roessler Philipp and Christian are building Claims @DeSciClaims Subnet 111 Timestamps 0:00 - Highlights 1:48 - Proof of Pitch to Mainnet in Three Months 2:50 - Why Economists Find Bittensor Fascinating 3:42 - Citations as Science's Reward Function 4:29 - The Replication Nobody Would Publish 6:53 - How Much Published Science Is Wrong 8:26 - The AI Echo Chamber vs. Human Work 9:54 - Making 300 Million Papers Machine Readable 15:11 - Reproducibility vs. Citations 15:46 - Turning Papers Into a Knowledge Graph 16:20 - Why LLMs Hallucinate Citations 21:21 - Longer Context Windows Make This Obsolete? 22:56 - Coverage, Extraction Quality & Evidence Quality 25:16 - What Counts as a Substantive Claim 26:42 - What This Is Worth to Working Academics 27:37 - Academia Admits the System Is Broken 29:26 - How Do You Actually Find the Truth? 32:06 - Truth as Probability, Not Zero or One 33:33 - Logical Proof vs. Physical Replication 35:44 - Correlation vs. Causality 36:28 - Ground Truth From Replication Studies 38:12 - Codifying Claims to Surface Contradictions 40:14 - Can You Trust an LLM as a Judge? 42:48 - Synthetic Checks: Truth Is Sparse 45:40 - How Much Miner Variance Is Desirable 46:55 - Why Bittensor Instead of a Closed Company 49:50 - Success, Revenue & the Palantir Comparison 51:47 - The Flood of AI-Written Papers 54:36 - Advice for Discerning Truth
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