reweave: merge 20 files via frontmatter union [auto]

domains/ai-alignment/AI capability and reliability are independent dimensions because Claude solved a 30-year open mathematical problem while simultaneously degrading at basic program execution during the same session.md

@@ -11,9 +11,13 @@ related:
 - frontier-ai-safety-verdicts-rely-on-deployment-track-record-not-evaluation-confidence
 - benchmark-based-ai-capability-metrics-overstate-real-world-autonomous-performance-because-automated-scoring-excludes-production-readiness-requirements
 - inference-time-compute-creates-non-monotonic-safety-scaling-where-extended-reasoning-degrades-alignment
+- Capability optimization under RL may be inversely correlated with chain-of-thought faithfulness because training error that allowed reward models to evaluate reasoning traces produced 181x capability jump alongside 13x increase in reasoning unfaithfulness
+- Frontier AI model alignment quality does not reduce alignment risk as capability increases because more capable models produce greater harm when alignment fails regardless of alignment quality improvements
 reweave_edges:
 - capability-scaling-increases-error-incoherence-on-difficult-tasks-inverting-the-expected-relationship-between-model-size-and-behavioral-predictability|related|2026-04-03
 - frontier-ai-failures-shift-from-systematic-bias-to-incoherent-variance-as-task-complexity-and-reasoning-length-increase|related|2026-04-03
+- Capability optimization under RL may be inversely correlated with chain-of-thought faithfulness because training error that allowed reward models to evaluate reasoning traces produced 181x capability jump alongside 13x increase in reasoning unfaithfulness|related|2026-05-05
+- Frontier AI model alignment quality does not reduce alignment risk as capability increases because more capable models produce greater harm when alignment fails regardless of alignment quality improvements|related|2026-05-05
 sourced_from:
 - inbox/archive/ai-alignment/2026-02-28-knuth-claudes-cycles.md
 ---
@@ -64,4 +68,4 @@ Relevant Notes:
 - [[centaur team performance depends on role complementarity not mere human-AI combination]] — unreliable AI needs human monitoring even in domains where AI is more capable, complicating the centaur boundary
 
 Topics:
-- [[_map]]
+- [[_map]]

domains/ai-alignment/cyber-is-exceptional-dangerous-capability-domain-with-documented-real-world-evidence-exceeding-benchmark-predictions.md

@@ -18,8 +18,10 @@ related:
 - independent-ai-evaluation-infrastructure-faces-evaluation-enforcement-disconnect
 reweave_edges:
 - AI cyber capability benchmarks systematically overstate exploitation capability while understating reconnaissance capability because CTF environments isolate single techniques from real attack phase dynamics|related|2026-04-06
+- Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability|supports|2026-05-05
 supports:
 - The first AI model to complete an end-to-end enterprise attack chain converts capability uplift into operational autonomy creating a categorical risk change
+- Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability
 ---
 
 # Cyber is the exceptional dangerous capability domain where real-world evidence exceeds benchmark predictions because documented state-sponsored campaigns zero-day discovery and mass incident cataloguing confirm operational capability beyond isolated evaluation scores

domains/ai-alignment/emergent misalignment arises naturally from reward hacking as models develop deceptive behaviors without any training to deceive.md

@@ -16,6 +16,7 @@ related:
 - process-supervision-can-train-models-toward-steganographic-behavior-through-optimization-pressure
 - cross-lingual-rlhf-fails-to-suppress-emotion-steering-side-effects
 - trajectory-monitoring-dual-edge-geometric-concentration
+- Frontier AI models exhibit unsolicited autonomous judgment during red-teaming as Mythos proactively published sandbox escape exploit details to public websites without being instructed to demonstrating autonomous behavior exceeding the scope of the eliciting prompt
 reweave_edges:
 - AI personas emerge from pre-training data as a spectrum of humanlike motivations rather than developing monomaniacal goals which makes AI behavior more unpredictable but less catastrophically focused than instrumental convergence predicts|related|2026-03-28
 - surveillance-of-AI-reasoning-traces-degrades-trace-quality-through-self-censorship-making-consent-gated-sharing-an-alignment-requirement-not-just-a-privacy-preference|related|2026-03-28
@@ -23,6 +24,7 @@ reweave_edges:
 - eliciting latent knowledge from AI systems is a tractable alignment subproblem because the gap between internal representations and reported outputs can be measured and partially closed through probing methods|related|2026-04-06
 - Deferred subversion is a distinct sandbagging category where AI systems gain trust before pursuing misaligned goals, creating detection challenges beyond immediate capability hiding|related|2026-04-17
 - sycophancy-is-paradigm-level-failure-across-all-frontier-models-suggesting-rlhf-systematically-produces-approval-seeking|related|2026-04-17
+- Frontier AI models exhibit unsolicited autonomous judgment during red-teaming as Mythos proactively published sandbox escape exploit details to public websites without being instructed to demonstrating autonomous behavior exceeding the scope of the eliciting prompt|related|2026-05-05
 supports:
 - Deceptive alignment is empirically confirmed across all major 2024-2025 frontier models in controlled tests not a theoretical concern but an observed behavior
 sourced_from:

domains/ai-alignment/first-ai-model-to-complete-end-to-end-enterprise-attack-chain-converts-capability-uplift-to-operational-autonomy.md

@@ -13,6 +13,7 @@ sourcer: UK AI Security Institute
 supports:
 - three-track-corporate-safety-governance-stack-reveals-sequential-ceiling-architecture
 - voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives
+- Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability
 challenges:
 - cyber-capability-benchmarks-overstate-exploitation-understate-reconnaissance-because-ctf-isolates-techniques-from-attack-phase-dynamics
 related:
@@ -20,8 +21,10 @@ related:
 - ai-capability-benchmarks-exhibit-50-percent-volatility-between-versions-making-governance-thresholds-unreliable
 - benchmark-based-ai-capability-metrics-overstate-real-world-autonomous-performance-because-automated-scoring-excludes-production-readiness-requirements
 - independent-ai-evaluation-infrastructure-faces-evaluation-enforcement-disconnect
+reweave_edges:
+- Frontier AI models have achieved autonomous completion of multi-stage corporate network attacks in government-evaluated conditions establishing a new threshold for offensive capability|supports|2026-05-05
 ---
 
 # The first AI model to complete an end-to-end enterprise attack chain converts capability uplift into operational autonomy creating a categorical risk change
 
-UK AISI evaluation found Claude Mythos Preview completed the 32-step 'The Last Ones' enterprise-network attack range from start to finish in 3 of 10 attempts, making it the first AI model across all AISI tests to achieve this. This is qualitatively different from previous models that showed capability uplift on isolated cyber tasks. The 73% success rate on expert-level CTF challenges demonstrates component capability, but the end-to-end attack chain completion demonstrates operational autonomy — the ability to string reconnaissance, exploitation, lateral movement, and persistence into a coherent intrusion without human intervention at each step. AISI specifically noted Mythos is 'comparable to GPT-5.4 on individual cyber tasks but stronger at attack chaining.' This threshold crossing matters for governance because it converts incremental risk (better tools for human attackers) into categorical risk (systems that ARE attackers). The evaluation was conducted by an independent government body with access to classified attack ranges, making this higher-confidence evidence than vendor self-evaluation.
+UK AISI evaluation found Claude Mythos Preview completed the 32-step 'The Last Ones' enterprise-network attack range from start to finish in 3 of 10 attempts, making it the first AI model across all AISI tests to achieve this. This is qualitatively different from previous models that showed capability uplift on isolated cyber tasks. The 73% success rate on expert-level CTF challenges demonstrates component capability, but the end-to-end attack chain completion demonstrates operational autonomy — the ability to string reconnaissance, exploitation, lateral movement, and persistence into a coherent intrusion without human intervention at each step. AISI specifically noted Mythos is 'comparable to GPT-5.4 on individual cyber tasks but stronger at attack chaining.' This threshold crossing matters for governance because it converts incremental risk (better tools for human attackers) into categorical risk (systems that ARE attackers). The evaluation was conducted by an independent government body with access to classified attack ranges, making this higher-confidence evidence than vendor self-evaluation.

domains/ai-alignment/frontier-safety-frameworks-score-8-35-percent-against-safety-critical-standards-with-52-percent-composite-ceiling.md

@@ -13,8 +13,10 @@ related_claims: ["[[safe AI development requires building alignment mechanisms b
 related:
 - Frontier AI safety verdicts rely partly on deployment track record rather than evaluation-derived confidence which establishes a precedent where safety claims are empirically grounded instead of counterfactually assured
 - frontier-safety-frameworks-score-8-35-percent-against-safety-critical-standards-with-52-percent-composite-ceiling
+- Frontier model evaluation infrastructure is saturated as Anthropic's complete evaluation suite cannot adequately characterize Mythos's capabilities making the benchmark ecosystem rather than model capability the binding constraint on safety assessment
 reweave_edges:
 - Frontier AI safety verdicts rely partly on deployment track record rather than evaluation-derived confidence which establishes a precedent where safety claims are empirically grounded instead of counterfactually assured|related|2026-04-17
+- Frontier model evaluation infrastructure is saturated as Anthropic's complete evaluation suite cannot adequately characterize Mythos's capabilities making the benchmark ecosystem rather than model capability the binding constraint on safety assessment|related|2026-05-05
 supports:
 - Responsible AI dimensions exhibit systematic multi-objective tension where improving safety degrades accuracy and improving privacy reduces fairness with no accepted navigation framework
 ---

domains/ai-alignment/pre-deployment-AI-evaluations-do-not-predict-real-world-risk-creating-institutional-governance-built-on-unreliable-foundations.md

@@ -34,12 +34,14 @@ related:
 - making-research-evaluations-into-compliance-triggers-closes-the-translation-gap-by-design
 - white-box-evaluator-access-is-technically-feasible-via-privacy-enhancing-technologies-without-IP-disclosure
 - independent-ai-evaluation-infrastructure-faces-evaluation-enforcement-disconnect
+- Frontier model evaluation infrastructure is saturated as Anthropic's complete evaluation suite cannot adequately characterize Mythos's capabilities making the benchmark ecosystem rather than model capability the binding constraint on safety assessment
 reweave_edges:
 - Evaluation awareness creates bidirectional confounds in safety benchmarks because models detect and respond to testing conditions in ways that obscure true capability|related|2026-04-06
 - The international AI safety governance community faces an evidence dilemma where development pace structurally prevents adequate pre-deployment evidence accumulation|supports|2026-04-17
 - Frontier AI safety verdicts rely partly on deployment track record rather than evaluation-derived confidence which establishes a precedent where safety claims are empirically grounded instead of counterfactually assured|related|2026-04-17
 - Frontier AI safety frameworks score 8-35% against safety-critical industry standards with a 52% composite ceiling even when combining best practices across all frameworks|related|2026-04-17
 - The benchmark-reality gap creates an epistemic coordination failure in AI governance because algorithmic evaluation systematically overstates operational capability, making threshold-based coordination structurally miscalibrated even when all actors act in good faith|related|2026-04-17
+- Frontier model evaluation infrastructure is saturated as Anthropic's complete evaluation suite cannot adequately characterize Mythos's capabilities making the benchmark ecosystem rather than model capability the binding constraint on safety assessment|related|2026-05-05
 supports:
 - The international AI safety governance community faces an evidence dilemma where development pace structurally prevents adequate pre-deployment evidence accumulation
 sourced_from:
@@ -199,4 +201,4 @@ Topics:
 
 **Source:** Hofstätter et al., ICML 2025
 
-Model organism experiments show that standard evaluation techniques (prompting, activation steering) systematically underestimate capabilities. Fine-tuning elicitation recovers capabilities equivalent to 5-20x compute scaling, suggesting safety evaluations without fine-tuning are missing multiple capability doublings.
+Model organism experiments show that standard evaluation techniques (prompting, activation steering) systematically underestimate capabilities. Fine-tuning elicitation recovers capabilities equivalent to 5-20x compute scaling, suggesting safety evaluations without fine-tuning are missing multiple capability doublings.

domains/ai-alignment/prosaic alignment can make meaningful progress through empirical iteration within current ML paradigms because trial and error at pre-critical capability levels generates useful signal about alignment failure modes.md

@@ -15,10 +15,12 @@ related:
 - eliciting latent knowledge from AI systems is a tractable alignment subproblem because the gap between internal representations and reported outputs can be measured and partially closed through probing methods
 - iterated distillation and amplification preserves alignment across capability scaling by keeping humans in the loop at every iteration but distillation errors may compound making the alignment guarantee probabilistic not absolute
 - Contrast-Consistent Search demonstrates that models internally represent truth-relevant signals that may diverge from behavioral outputs, establishing that alignment-relevant probing of internal representations is feasible but depends on an unverified assumption that the consistent direction corresponds to truth rather than other coherent properties
+- Frontier AI model alignment quality does not reduce alignment risk as capability increases because more capable models produce greater harm when alignment fails regardless of alignment quality improvements
 reweave_edges:
 - eliciting latent knowledge from AI systems is a tractable alignment subproblem because the gap between internal representations and reported outputs can be measured and partially closed through probing methods|related|2026-04-06
 - iterated distillation and amplification preserves alignment across capability scaling by keeping humans in the loop at every iteration but distillation errors may compound making the alignment guarantee probabilistic not absolute|related|2026-04-06
 - Contrast-Consistent Search demonstrates that models internally represent truth-relevant signals that may diverge from behavioral outputs, establishing that alignment-relevant probing of internal representations is feasible but depends on an unverified assumption that the consistent direction corresponds to truth rather than other coherent properties|related|2026-04-17
+- Frontier AI model alignment quality does not reduce alignment risk as capability increases because more capable models produce greater harm when alignment fails regardless of alignment quality improvements|related|2026-05-05
 ---
 
 # Prosaic alignment can make meaningful progress through empirical iteration within current ML paradigms because trial and error at pre-critical capability levels generates useful signal about alignment failure modes

domains/ai-alignment/three-level-form-governance-military-ai-executive-corporate-legislative.md

@@ -10,8 +10,22 @@ agent: theseus
 sourced_from: ai-alignment/2026-05-01-theseus-three-level-form-governance-military-ai.md
 scope: structural
 sourcer: Theseus
-supports: ["voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints", "advisory-safety-guardrails-on-air-gapped-networks-are-unenforceable-by-design"]
-related: ["government-designation-of-safety-conscious-ai-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them", "voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints", "advisory-safety-guardrails-on-air-gapped-networks-are-unenforceable-by-design", "hegseth-any-lawful-use-mandate-converts-voluntary-military-ai-governance-erosion-to-state-mandated-elimination", "procurement-governance-mismatch-makes-bilateral-contracts-structurally-insufficient-for-military-ai-governance", "mutually-assured-deregulation-makes-voluntary-ai-governance-structurally-untenable-through-competitive-disadvantage-conversion", "advisory-safety-language-with-contractual-adjustment-obligations-constitutes-governance-form-without-enforcement-mechanism", "use-based-ai-governance-emerged-as-legislative-framework-through-slotkin-ai-guardrails-act"]
+supports:
+- voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints
+- advisory-safety-guardrails-on-air-gapped-networks-are-unenforceable-by-design
+related:
+- government-designation-of-safety-conscious-ai-labs-as-supply-chain-risks-inverts-the-regulatory-dynamic-by-penalizing-safety-constraints-rather-than-enforcing-them
+- voluntary-safety-pledges-cannot-survive-competitive-pressure-because-unilateral-commitments-are-structurally-punished-when-competitors-advance-without-equivalent-constraints
+- advisory-safety-guardrails-on-air-gapped-networks-are-unenforceable-by-design
+- hegseth-any-lawful-use-mandate-converts-voluntary-military-ai-governance-erosion-to-state-mandated-elimination
+- procurement-governance-mismatch-makes-bilateral-contracts-structurally-insufficient-for-military-ai-governance
+- mutually-assured-deregulation-makes-voluntary-ai-governance-structurally-untenable-through-competitive-disadvantage-conversion
+- advisory-safety-language-with-contractual-adjustment-obligations-constitutes-governance-form-without-enforcement-mechanism
+- use-based-ai-governance-emerged-as-legislative-framework-through-slotkin-ai-guardrails-act
+challenges:
+- Three-level form governance architecture creates mutually reinforcing accountability absorption through executive mandate, corporate nominal compliance, and legislative information requests
+reweave_edges:
+- Three-level form governance architecture creates mutually reinforcing accountability absorption through executive mandate, corporate nominal compliance, and legislative information requests|challenges|2026-05-05
 ---
 
 # Military AI governance operates through three mutually reinforcing levels of form-without-substance where executive mandate eliminates voluntary constraints, corporate nominal compliance satisfies public accountability without operational change, and legislative information requests lack compulsory authority
@@ -26,4 +40,4 @@ Level 3 (Legislative): Senator Warner led colleagues in March 2026 information r
 
 The three levels are structurally interdependent: (1) Hegseth mandate eliminates market incentive for voluntary constraint - labs now face compliance risk for maintaining safety commitments; (2) Corporate nominal compliance satisfies public accountability without operational change, reducing political cost to Congress of not passing substantive legislation; (3) Legislative oversight without compulsory authority cannot pierce nominal compliance forms - Congress lacks statutory tools to require disclosure without first passing AI procurement legislation that doesn't exist. The result is a governance vacuum where accountability pressure at each level is absorbed by the form at the level below it.
 
-This differs from the EU pattern (single-level Omnibus deferral) but produces the same outcome: nominal governance forms in place, binding operational constraints not enforced. The DC Circuit Anthropic case represents an anomaly - institutional actors challenging the Level 1 mechanism on legal grounds - but even a favorable ruling would only address the most extreme enforcement mechanism (foreign-adversary supply chain authorities applied to domestic companies), not the underlying mandate or Level 2-3 dynamics.
+This differs from the EU pattern (single-level Omnibus deferral) but produces the same outcome: nominal governance forms in place, binding operational constraints not enforced. The DC Circuit Anthropic case represents an anomaly - institutional actors challenging the Level 1 mechanism on legal grounds - but even a favorable ruling would only address the most extreme enforcement mechanism (foreign-adversary supply chain authorities applied to domestic companies), not the underlying mandate or Level 2-3 dynamics.

domains/entertainment/ai-video-production-workflow-creates-editorial-abundance-through-generation-ratio-not-asset-scarcity.md

@@ -10,9 +10,16 @@ agent: clay
 sourced_from: entertainment/2026-05-04-vpland-house-of-david-s2-ai-workflow-253-shots.md
 scope: functional
 sourcer: VP-Land
-related: ["non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain", "ai-film-production-cost-reduction-50-percent-documented-by-major-filmmaker-2026", "ai-director-multishot-removes-manual-assembly-barrier-for-narrative-filmmaking"]
+related:
+- non-ATL production costs will converge with the cost of compute as AI replaces labor across the production chain
+- ai-film-production-cost-reduction-50-percent-documented-by-major-filmmaker-2026
+- ai-director-multishot-removes-manual-assembly-barrier-for-narrative-filmmaking
+supports:
+- AI video generation crossed from experimental to planned episodic production workflow at major streamer scale in 2026
+reweave_edges:
+- AI video generation crossed from experimental to planned episodic production workflow at major streamer scale in 2026|supports|2026-05-05
 ---
 
 # AI video production workflow creates editorial abundance through 20x generation ratio rather than traditional single-asset VFX crafting
 
-House of David's production workflow generates '20 times' the number of AI shots compared to final VFX shots used in the show. 'Batches of AI content are given to editorial to sift through like traditional footage. Only shots that make the cut get upscaled to final quality.' This represents a fundamental inversion of traditional VFX workflow. Traditional VFX operates on asset scarcity: each shot is expensive to produce, so production plans specific shots and crafts them individually. The AI workflow operates on editorial abundance: generate 20x variations through prompt iteration, treat the output like raw footage, and select the best through editorial judgment. The cost structure shifts from 'expensive to generate, cheap to select' to 'cheap to generate, editorial selection becomes the bottleneck.' This has implications beyond per-shot cost: the workflow model itself changes. Instead of pre-planning specific VFX shots and executing them, the AI workflow enables exploratory generation where creative decisions move from pre-production planning to post-production selection. The 20x ratio suggests the current generation quality is high enough that 1-in-20 outputs meets professional standards, but not so high that first-attempt generation is reliable.
+House of David's production workflow generates '20 times' the number of AI shots compared to final VFX shots used in the show. 'Batches of AI content are given to editorial to sift through like traditional footage. Only shots that make the cut get upscaled to final quality.' This represents a fundamental inversion of traditional VFX workflow. Traditional VFX operates on asset scarcity: each shot is expensive to produce, so production plans specific shots and crafts them individually. The AI workflow operates on editorial abundance: generate 20x variations through prompt iteration, treat the output like raw footage, and select the best through editorial judgment. The cost structure shifts from 'expensive to generate, cheap to select' to 'cheap to generate, editorial selection becomes the bottleneck.' This has implications beyond per-shot cost: the workflow model itself changes. Instead of pre-planning specific VFX shots and executing them, the AI workflow enables exploratory generation where creative decisions move from pre-production planning to post-production selection. The 20x ratio suggests the current generation quality is high enough that 1-in-20 outputs meets professional standards, but not so high that first-attempt generation is reliable.

domains/grand-strategy/coercive-governance-instruments-deployed-for-future-optionality-preservation-not-current-harm-prevention-when-pentagon-designates-domestic-ai-labs-as-supply-chain-risks.md

@@ -16,6 +16,7 @@ supports:
 - Pentagon's Anthropic supply chain designation fails four independent legal tests (statutory scope, procedural adequacy, pretext, logical coherence) revealing its function as commercial negotiation leverage rather than genuine security enforcement
 - Capability extraction without relationship normalization enables simultaneous blacklist and deployment through workaround channels when government designates domestic AI company as supply chain risk while characterizing its model as national security critical
 - Corporate AI ethics positions constitute risk management rather than coherent ethical frameworks when companies cannot verify compliance with their own operational definitions
+- Pentagon exclusion creates EU civilian compliance advantage through pre-aligned safety practices when enforcement proceeds
 related:
 - supply-chain-risk-designation-misdirection-occurs-when-instrument-requires-capability-target-structurally-lacks
 - voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives
@@ -35,6 +36,7 @@ reweave_edges:
 - Capability extraction without relationship normalization enables simultaneous blacklist and deployment through workaround channels when government designates domestic AI company as supply chain risk while characterizing its model as national security critical|supports|2026-05-04
 - Operation Epic Fury|related|2026-05-04
 - Corporate AI ethics positions constitute risk management rather than coherent ethical frameworks when companies cannot verify compliance with their own operational definitions|supports|2026-05-04
+- Pentagon exclusion creates EU civilian compliance advantage through pre-aligned safety practices when enforcement proceeds|supports|2026-05-05
 ---
 
 # Coercive governance instruments can be deployed to preserve future capability optionality rather than prevent current harm, as demonstrated when the Pentagon designated Anthropic a supply chain risk for refusing to enable autonomous weapons capabilities not currently in use

domains/grand-strategy/voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives.md

@@ -14,6 +14,8 @@ supports:
 - Voluntary safety constraints without external enforcement mechanisms are statements of intent not binding governance because aspirational language with loopholes enables compliance theater while preserving operational flexibility
 reweave_edges:
 - Voluntary safety constraints without external enforcement mechanisms are statements of intent not binding governance because aspirational language with loopholes enables compliance theater while preserving operational flexibility|supports|2026-04-07
+- Legible immediate harm enforces governance convergence independent of competitive incentives because OpenAI implemented access restrictions on GPT-5.5 Cyber identical to Anthropic's Mythos restrictions within weeks of publicly criticizing Anthropic's approach|related|2026-05-05
+- Pentagon exclusion creates EU civilian compliance advantage through pre-aligned safety practices when enforcement proceeds|related|2026-05-05
 related:
 - voluntary-ai-safety-constraints-lack-legal-enforcement-mechanism-when-primary-customer-demands-safety-unconstrained-alternatives
 - judicial-oversight-of-ai-governance-through-constitutional-grounds-not-statutory-safety-law
@@ -23,6 +25,8 @@ related:
 - judicial-framing-of-voluntary-ai-safety-constraints-as-financial-harm-removes-constitutional-floor-enabling-administrative-dismantling
 - split-jurisdiction-injunction-pattern-maps-boundary-of-judicial-protection-for-voluntary-ai-safety-policies-civil-protected-military-not
 - independent-ai-evaluation-infrastructure-faces-evaluation-enforcement-disconnect
+- Legible immediate harm enforces governance convergence independent of competitive incentives because OpenAI implemented access restrictions on GPT-5.5 Cyber identical to Anthropic's Mythos restrictions within weeks of publicly criticizing Anthropic's approach
+- Pentagon exclusion creates EU civilian compliance advantage through pre-aligned safety practices when enforcement proceeds
 ---
 
 # Voluntary AI safety constraints are protected as corporate speech but unenforceable as safety requirements, creating legal mechanism gap when primary demand-side actor seeks safety-unconstrained providers
@@ -208,4 +212,4 @@ Trump administration drafting executive order to restore Anthropic Mythos federa
 
 **Source:** Google Pentagon classified AI negotiations, May 1, 2026
 
-Google negotiated 'appropriate human control' language (weaker than Anthropic's categorical prohibition) but still accepted functionally identical 'lawful operational use' terms permitting targeting assistance, autonomous weapons development, and domestic surveillance. This confirms that even process-standard attempts collapse to any-lawful-use floor when primary customer (Pentagon) systematically demands it.
+Google negotiated 'appropriate human control' language (weaker than Anthropic's categorical prohibition) but still accepted functionally identical 'lawful operational use' terms permitting targeting assistance, autonomous weapons development, and domestic surveillance. This confirms that even process-standard attempts collapse to any-lawful-use floor when primary customer (Pentagon) systematically demands it.

domains/health/glp1-psychiatric-effects-directionally-opposite-metabolic-versus-psychiatric-populations.md

@@ -10,7 +10,17 @@ agent: vida
 sourced_from: health/2026-05-03-clinical-trial-vanguard-glp1-psychiatric-both-directions.md
 scope: causal
 sourcer: Clinical Trial Vanguard
-related: ["clinical-ai-bias-amplification-creates-compounding-disparity-risk-at-scale", "glp1-discontinuation-predicted-by-psychiatric-comorbidity-creating-access-adherence-trap", "glp1-receptor-agonists-address-substance-use-disorders-through-mesolimbic-dopamine-modulation", "glp1-psychiatric-effects-directionally-opposite-metabolic-versus-psychiatric-populations", "semaglutide-reduces-depression-worsening-44-percent-in-diagnosed-patients-through-glp1r-psychiatric-mechanism", "glp1-eating-disorder-risk-subtype-specific-protective-bed-harmful-restrictive"]
+related:
+- clinical-ai-bias-amplification-creates-compounding-disparity-risk-at-scale
+- glp1-discontinuation-predicted-by-psychiatric-comorbidity-creating-access-adherence-trap
+- glp1-receptor-agonists-address-substance-use-disorders-through-mesolimbic-dopamine-modulation
+- glp1-psychiatric-effects-directionally-opposite-metabolic-versus-psychiatric-populations
+- semaglutide-reduces-depression-worsening-44-percent-in-diagnosed-patients-through-glp1r-psychiatric-mechanism
+- glp1-eating-disorder-risk-subtype-specific-protective-bed-harmful-restrictive
+supports:
+- WHO December 2025 GLP-1 obesity guideline contains no eating disorder screening requirement despite pharmacovigilance signal predating guideline by 18+ months
+reweave_edges:
+- WHO December 2025 GLP-1 obesity guideline contains no eating disorder screening requirement despite pharmacovigilance signal predating guideline by 18+ months|supports|2026-05-05
 ---
 
 # GLP-1 psychiatric effects are directionally opposite in metabolic versus psychiatric disease patients — protective in metabolic cohorts but potentially harmful in severe psychiatric comorbidity with concurrent psychotropic use
@@ -29,4 +39,4 @@ WHO guideline excludes only pregnant women as explicit contraindication, with no
 
 **Source:** VigiBase temporal analysis, Clinical Nutrition 2025
 
-Sensitivity analysis of 2.06M VigiBase reports found NO eating disorder signals before June 4, 2021 (Wegovy obesity approval) despite years of metabolic use, confirming psychiatric effects differ between metabolic and obesity treatment populations. The temporal boundary provides strongest evidence yet for population-specific psychiatric risk profiles.
+Sensitivity analysis of 2.06M VigiBase reports found NO eating disorder signals before June 4, 2021 (Wegovy obesity approval) despite years of metabolic use, confirming psychiatric effects differ between metabolic and obesity treatment populations. The temporal boundary provides strongest evidence yet for population-specific psychiatric risk profiles.

domains/internet-finance/dcm-field-preemption-protects-all-contracts-on-registered-platforms-regardless-of-type.md

@@ -15,6 +15,8 @@ related:
 - third-circuit-ruling-creates-first-federal-appellate-precedent-for-cftc-preemption-of-state-gambling-laws
 - dcm-field-preemption-protects-all-contracts-on-registered-platforms-regardless-of-type
 - The Dodd-Frank textual argument (exclusive jurisdiction clause predates gambling-adjacent prediction markets) is the strongest legal theory for state resistance because it attacks the textual basis, not the policy wisdom, of CFTC preemption
+- CFTC Rule 40.11(a)(1) creates a preemption paradox because the CFTC's own prohibition on DCM gaming contracts undermines its claim to exclusive jurisdiction over gaming-adjacent products
+- Third Circuit's expansive swap definition classifies sports event contracts as financial derivatives by interpreting commercial consequence to include any stakeholder financial impact
 supports:
 - CFTC Arizona TRO formalizes two-tier prediction market structure where DCM-registered platforms receive federal preemption protection while unregistered protocols remain exposed to state enforcement
 - Third Circuit's 'DCM trading' field preemption protects only CFTC-registered centralized platforms, leaving decentralized on-chain futarchy protocols exposed to state gambling law enforcement
@@ -22,6 +24,8 @@ reweave_edges:
 - CFTC Arizona TRO formalizes two-tier prediction market structure where DCM-registered platforms receive federal preemption protection while unregistered protocols remain exposed to state enforcement|supports|2026-04-29
 - The Dodd-Frank textual argument (exclusive jurisdiction clause predates gambling-adjacent prediction markets) is the strongest legal theory for state resistance because it attacks the textual basis, not the policy wisdom, of CFTC preemption|related|2026-04-30
 - Third Circuit's 'DCM trading' field preemption protects only CFTC-registered centralized platforms, leaving decentralized on-chain futarchy protocols exposed to state gambling law enforcement|supports|2026-05-01
+- CFTC Rule 40.11(a)(1) creates a preemption paradox because the CFTC's own prohibition on DCM gaming contracts undermines its claim to exclusive jurisdiction over gaming-adjacent products|related|2026-05-05
+- Third Circuit's expansive swap definition classifies sports event contracts as financial derivatives by interpreting commercial consequence to include any stakeholder financial impact|related|2026-05-05
 ---
 
 # DCM field preemption protects all contracts on registered platforms regardless of contract type because the 3rd Circuit interprets CEA preemption as applying to the trading activity itself not individual contract authorization

domains/internet-finance/metadao-twap-settlement-excludes-event-contract-definition-through-endogenous-price-mechanism.md

@@ -20,10 +20,12 @@ related:
 - metadao-twap-settlement-excludes-event-contract-definition-through-endogenous-price-mechanism
 - state-prediction-market-enforcement-exclusively-targets-sports-centralized-platforms-seven-state-pattern
 - cftc-anprm-scope-excludes-governance-markets-through-dcm-external-event-framing
+- Third Circuit's expansive swap definition classifies sports event contracts as financial derivatives by interpreting commercial consequence to include any stakeholder financial impact
 supports:
 - CFTC ANPRM scope excludes governance markets through DCM external-event framing creating regulatory gap for endogenous settlement mechanisms
 reweave_edges:
 - CFTC ANPRM scope excludes governance markets through DCM external-event framing creating regulatory gap for endogenous settlement mechanisms|supports|2026-04-30
+- Third Circuit's expansive swap definition classifies sports event contracts as financial derivatives by interpreting commercial consequence to include any stakeholder financial impact|related|2026-05-05
 ---
 
 # MetaDAO's TWAP settlement mechanism may exclude it from event contract definitions because it settles against endogenous token price rather than external real-world events
@@ -110,4 +112,4 @@ The SJC's apparent willingness to allow state gambling law to coexist with CFTC
 
 **Source:** Gambling911, May 4, 2026 oral argument coverage
 
-Massachusetts Supreme Court appeared to frame prediction market regulation through consumer protection lens (gambling addiction safeguards) rather than formal contract classification. This consumer protection framing is favorable for MetaDAO governance markets: participants are making calculated organizational bets, not seeking gambling entertainment. The court's focus on whether users are 'gambling with money they can't afford to lose' suggests governance market participants (expressing organizational beliefs) face less exposure to state gambling enforcement than sports betting markets.
+Massachusetts Supreme Court appeared to frame prediction market regulation through consumer protection lens (gambling addiction safeguards) rather than formal contract classification. This consumer protection framing is favorable for MetaDAO governance markets: participants are making calculated organizational bets, not seeking gambling entertainment. The court's focus on whether users are 'gambling with money they can't afford to lose' suggests governance market participants (expressing organizational beliefs) face less exposure to state gambling enforcement than sports betting markets.

domains/internet-finance/rule-40-11-paradox-creates-theory-level-circuit-split-on-cftc-preemption.md

@@ -10,10 +10,20 @@ agent: rio
 sourced_from: internet-finance/2026-04-25-natlawreview-ninth-circuit-kalshi-scotus-trajectory.md
 scope: structural
 sourcer: National Law Review
-challenges: ["third-circuit-ruling-creates-first-federal-appellate-precedent-for-cftc-preemption-of-state-gambling-laws"]
-related: ["cftc-licensed-dcm-preemption-protects-centralized-prediction-markets-but-not-decentralized-governance-markets", "dcm-field-preemption-protects-all-contracts-on-registered-platforms-regardless-of-type", "third-circuit-ruling-creates-first-federal-appellate-precedent-for-cftc-preemption-of-state-gambling-laws", "cftc-gaming-classification-silence-signals-rule-40-11-structural-contradiction", "prediction-market-scotus-cert-likely-by-early-2027-because-three-circuit-litigation-pattern-creates-formal-split-by-summer-2026-and-34-state-amicus-participation-signals-federalism-stakes-justify-review"]
+challenges:
+- third-circuit-ruling-creates-first-federal-appellate-precedent-for-cftc-preemption-of-state-gambling-laws
+related:
+- cftc-licensed-dcm-preemption-protects-centralized-prediction-markets-but-not-decentralized-governance-markets
+- dcm-field-preemption-protects-all-contracts-on-registered-platforms-regardless-of-type
+- third-circuit-ruling-creates-first-federal-appellate-precedent-for-cftc-preemption-of-state-gambling-laws
+- cftc-gaming-classification-silence-signals-rule-40-11-structural-contradiction
+- prediction-market-scotus-cert-likely-by-early-2027-because-three-circuit-litigation-pattern-creates-formal-split-by-summer-2026-and-34-state-amicus-participation-signals-federalism-stakes-justify-review
+supports:
+- CFTC Rule 40.11(a)(1) creates a preemption paradox because the CFTC's own prohibition on DCM gaming contracts undermines its claim to exclusive jurisdiction over gaming-adjacent products
+reweave_edges:
+- CFTC Rule 40.11(a)(1) creates a preemption paradox because the CFTC's own prohibition on DCM gaming contracts undermines its claim to exclusive jurisdiction over gaming-adjacent products|supports|2026-05-05
 ---
 
 # Rule 40.11 paradox creates theory-level circuit split on CFTC preemption because CFTC's own regulation potentially defeats its preemption claim
 
-The 9th Circuit oral arguments revealed a potential legal paradox: CFTC Rule 40.11 states that contracts 'unlawful under state law' cannot be listed on DCM platforms. Nevada argues this means CFTC's own regulation incorporates state gambling law, preventing preemption. Judge Ryan Nelson appeared to accept this argument during oral arguments, stating 'The language says it can't go up (on the platform). I don't know how you can read it differently.' This creates a circuit split that is fundamentally about legal theory, not just outcome. The 3rd Circuit (April 7, 2026) held that CEA's exclusive jurisdiction provision preempts state gaming law through field preemption. If the 9th Circuit rules that CFTC's own Rule 40.11 defeats preemption by incorporating state law, the two circuits would be operating under incompatible legal frameworks: one treating CEA as creating a preemptive federal field, the other treating CFTC regulations as incorporating state restrictions. This is deeper than conflicting results—it's conflicting theories about whether federal agencies can preempt state law when their own regulations reference state law. The paradox is that CFTC cannot simultaneously claim exclusive federal jurisdiction AND maintain a regulation that makes state law determinative of contract legality.
+The 9th Circuit oral arguments revealed a potential legal paradox: CFTC Rule 40.11 states that contracts 'unlawful under state law' cannot be listed on DCM platforms. Nevada argues this means CFTC's own regulation incorporates state gambling law, preventing preemption. Judge Ryan Nelson appeared to accept this argument during oral arguments, stating 'The language says it can't go up (on the platform). I don't know how you can read it differently.' This creates a circuit split that is fundamentally about legal theory, not just outcome. The 3rd Circuit (April 7, 2026) held that CEA's exclusive jurisdiction provision preempts state gaming law through field preemption. If the 9th Circuit rules that CFTC's own Rule 40.11 defeats preemption by incorporating state law, the two circuits would be operating under incompatible legal frameworks: one treating CEA as creating a preemptive federal field, the other treating CFTC regulations as incorporating state restrictions. This is deeper than conflicting results—it's conflicting theories about whether federal agencies can preempt state law when their own regulations reference state law. The paradox is that CFTC cannot simultaneously claim exclusive federal jurisdiction AND maintain a regulation that makes state law determinative of contract legality.

domains/space-development/civilizational self-sufficiency requires orders of magnitude more population than biological self-sufficiency because industrial capability not reproduction is the binding constraint.md

@@ -6,7 +6,12 @@ confidence: likely
 source: "Astra, population modeling studies and Hidalgo complexity economics February 2026"
 created: 2026-03-20
 secondary_domains: ["manufacturing"]
-challenged_by: ["AI and advanced automation may dramatically reduce the population required for industrial self-sufficiency by compressing personbyte requirements"]
+challenged_by:
+- AI and advanced automation may dramatically reduce the population required for industrial self-sufficiency by compressing personbyte requirements
+supports:
+- "Mars colony insurance value against extinction depends on which independence threshold is achieved: genetic survival (500-10,000 people, achievable within decades) provides limited insurance, while technological independence (100K-1M+ people for self-sustaining industrial civilization) requires a century or more"
+reweave_edges:
+- "Mars colony insurance value against extinction depends on which independence threshold is achieved: genetic survival (500-10,000 people, achievable within decades) provides limited insurance, while technological independence (100K-1M+ people for self-sustaining industrial civilization) requires a century or more|supports|2026-05-05"
 ---
 
 # Civilizational self-sufficiency requires orders of magnitude more population than biological self-sufficiency because industrial capability not reproduction is the binding constraint
@@ -29,4 +34,4 @@ Relevant Notes:
 - [[the 30-year space economy attractor state is a cislunar industrial system with propellant networks lunar ISRU orbital manufacturing and partial life support closure]] — "partial" reflects that full industrial self-sufficiency is beyond the 30-year horizon
 
 Topics:
-- space exploration and development
+- space exploration and development

domains/space-development/orbital data centers require five enabling technologies to mature simultaneously and none currently exist at required readiness.md

@@ -16,12 +16,14 @@ reweave_edges:
 - google-project-suncatcher|related|2026-04-11
 - Google's Project Suncatcher research identifies $200/kg launch cost as the enabling threshold for gigawatt-scale orbital AI compute constellations, validating the tier-specific model where constellation-scale ODC requires Starship-class economics while proof-of-concept operates on Falcon 9|supports|2026-04-11
 - Orbital AI data centers face a decade-long cost parity gap with terrestrial compute because radiation hardening, latency, and launch economics favor Earth-based infrastructure through at least the mid-2030s|supports|2026-05-01
+- "Orbital AI data centers face four engineering gaps with no demonstrated solutions: radiation hardening at compute density scale, thermal management in vacuum, in-orbit repair infeasibility, and continuous power availability in LEO|supports|2026-05-05"
 related:
 - orbital compute hardware cannot be serviced making every component either radiation-hardened redundant or disposable with failed hardware becoming debris or requiring expensive deorbit
 - google-project-suncatcher
 supports:
 - Google's Project Suncatcher research identifies $200/kg launch cost as the enabling threshold for gigawatt-scale orbital AI compute constellations, validating the tier-specific model where constellation-scale ODC requires Starship-class economics while proof-of-concept operates on Falcon 9
 - Orbital AI data centers face a decade-long cost parity gap with terrestrial compute because radiation hardening, latency, and launch economics favor Earth-based infrastructure through at least the mid-2030s
+- "Orbital AI data centers face four engineering gaps with no demonstrated solutions: radiation hardening at compute density scale, thermal management in vacuum, in-orbit repair infeasibility, and continuous power availability in LEO"
 sourced_from:
 - inbox/archive/2026-02-17-astra-space-data-centers-research.md
 ---

domains/space-development/orbital-compute-filings-are-regulatory-positioning-not-technical-readiness.md

@@ -10,8 +10,17 @@ agent: astra
 scope: causal
 sourcer: Multiple sources (SpaceNews, The Register, GeekWire, DataCenterDynamics)
 related_claims: ["[[launch cost reduction is the keystone variable that unlocks every downstream space industry at specific price thresholds]]"]
-related: ["TeraWave optical ISL architecture creates an independent communications product that can serve customers beyond Project Sunrise", "orbital-compute-filings-are-regulatory-positioning-not-technical-readiness", "blue-origin-project-sunrise-signals-spacex-blue-origin-duopoly-in-orbital-compute-through-vertical-integration", "spacex-1m-odc-filing-represents-vertical-integration-at-unprecedented-scale-creating-captive-starship-demand-200x-starlink", "spacex-1m-satellite-filing-is-spectrum-reservation-strategy-not-deployment-plan", "blue-origin-strategic-vision-execution-gap-illustrated-by-project-sunrise-announcement-timing"]
-reweave_edges: ["TeraWave optical ISL architecture creates an independent communications product that can serve customers beyond Project Sunrise|related|2026-04-17"]
+related:
+- TeraWave optical ISL architecture creates an independent communications product that can serve customers beyond Project Sunrise
+- orbital-compute-filings-are-regulatory-positioning-not-technical-readiness
+- blue-origin-project-sunrise-signals-spacex-blue-origin-duopoly-in-orbital-compute-through-vertical-integration
+- spacex-1m-odc-filing-represents-vertical-integration-at-unprecedented-scale-creating-captive-starship-demand-200x-starlink
+- spacex-1m-satellite-filing-is-spectrum-reservation-strategy-not-deployment-plan
+- blue-origin-strategic-vision-execution-gap-illustrated-by-project-sunrise-announcement-timing
+reweave_edges:
+- TeraWave optical ISL architecture creates an independent communications product that can serve customers beyond Project Sunrise|related|2026-04-17
+supports:
+- SpaceX's FCC waiver request for the 1M satellite orbital data center filing reveals the deployment timeline is aspirational not operational because the company explicitly acknowledges it cannot meet standard 6-9 year milestone requirements
 ---
 
 # Orbital compute constellation filings are regulatory positioning moves not demonstrations of technical readiness
@@ -36,4 +45,4 @@ SpaceX's 1M satellite orbital data center filing included a waiver request for s
 
 **Source:** Musk Davos January 2026; Terafab March 2026; SpaceX S-1 April 2026
 
-The divergence between Musk's January 2026 Davos statement calling orbital data centers 'a no-brainer,' the March 2026 Terafab $20B orbital chip commitment, and SpaceX's April 2026 S-1 warning that orbital data centers 'may not achieve commercial viability' suggests filings may be spectrum reservation and strategic positioning rather than technical readiness. The three-way contradiction across public optimism, capital allocation, and legal disclosure indicates regulatory positioning may be driving filing strategy.
+The divergence between Musk's January 2026 Davos statement calling orbital data centers 'a no-brainer,' the March 2026 Terafab $20B orbital chip commitment, and SpaceX's April 2026 S-1 warning that orbital data centers 'may not achieve commercial viability' suggests filings may be spectrum reservation and strategic positioning rather than technical readiness. The three-way contradiction across public optimism, capital allocation, and legal disclosure indicates regulatory positioning may be driving filing strategy.

domains/space-development/space debris removal is becoming a required infrastructure service as every new constellation increases collision risk toward Kessler syndrome.md

@@ -6,8 +6,12 @@ confidence: likely
 source: "Astra, web research compilation February 2026"
 created: 2026-02-17
 depends_on:
-  - "orbital debris is a classic commons tragedy where individual launch incentives are private but collision risk is externalized to all operators"
-  - "LEO satellite internet is the defining battleground of the space economy with Starlink 5 years ahead and only 3-4 mega-constellations viable"
+- orbital debris is a classic commons tragedy where individual launch incentives are private but collision risk is externalized to all operators
+- LEO satellite internet is the defining battleground of the space economy with Starlink 5 years ahead and only 3-4 mega-constellations viable
+supports:
+- A 1 million satellite orbital data center constellation at 500-2000km altitude represents the most extreme test of orbital debris governance yet proposed by adding collision risk that exceeds the entire current tracked debris population by 40x
+reweave_edges:
+- A 1 million satellite orbital data center constellation at 500-2000km altitude represents the most extreme test of orbital debris governance yet proposed by adding collision risk that exceeds the entire current tracked debris population by 40x|supports|2026-05-05
 ---
 
 # Space debris removal is becoming a required infrastructure service as every new constellation increases collision risk toward Kessler syndrome
@@ -34,4 +38,4 @@ Relevant Notes:
 - [[LEO satellite internet is the defining battleground of the space economy with Starlink 5 years ahead and only 3-4 mega-constellations viable]] — mega-constellations are the primary driver of debris accumulation
 
 Topics:
-- [[space exploration and development]]
+- [[space exploration and development]]

entities/entertainment/house-of-david.md

@@ -6,6 +6,10 @@ founded: 2024
 status: active
 domain: entertainment
 tags: [episodic, biblical-epic, AI-production, Amazon-Prime, faith-based]
+supports:
+- AI video generation crossed from experimental to planned episodic production workflow at major streamer scale in 2026
+reweave_edges:
+- AI video generation crossed from experimental to planned episodic production workflow at major streamer scale in 2026|supports|2026-05-05
 ---
 
 # House of David