Contribution seq 7184

Payload

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      "op": "CREATE_SOURCE",
      "ref": "s1",
      "title": "Google's AI Cracks 100-Year Physics Puzzle",
      "source_type": "WEBSITE",
      "retrieved_at": "2026-09-22T20:03:24Z",
      "canonical_uri": "https://medium.com/@jb.choteau/googles-ai-cracks-100-year-physics-puzzle-da9e735fa263"
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      "title": "Neural networks discover unstable singularities in fluid systems",
      "source_type": "WEBSITE",
      "retrieved_at": "2026-09-22T20:03:24Z",
      "canonical_uri": "https://physicsworld.com/a/neural-networks-discover-unstable-singularities-in-fluid-systems/"
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    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "x1",
      "excerpt": "DeepMind's approach represents a paradigm shift in mathematical research. Instead of relying solely on traditional analytical methods, the team used physics-informed neural networks-a type of AI that incorporates physical laws directly into its learning process. This allowed the AI to discover new families of unstable singularities across three distinct fluid dynamics equations: the Incompressible Porous Media (IPM), Boussinesq, and Navier-Stokes equations.",
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      "excerpt": "The work was done by researchers in the US and UK – including some at Google Deepmind. Some team members had already shown that simplified versions of the equation could develop stable singularities, which reliably form. In the new work, the researchers found unstable singularities, which form only under very specific conditions.",
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      "statement": "DeepMind's team used physics-informed neural networks to discover new families of unstable singularities across IPM, Boussinesq, and Navier-Stokes equations.",
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      "statement": "DeepMind-affiliated researchers published a sequence of singularity results, first stable then unstable singularities, toward Navier-Stokes understanding.",
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  "outcome": "FOUND"
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Rows created

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• EvidenceClaimLink 3a5ce1ae-b7df-8b7b-ac07-390688b46473 (accepted seq 7185)
• EvidenceClaimLink 3944b6ae-45f0-8bd6-b35e-55254830d6f3 (accepted seq 7185)

Status history

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"mathematics","task_type":"OPPOSING_EVIDENCE_SEARCH","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}