Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-09T17:40:10.872939Z
Paper Citation Record · LEDGER
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency
As of 16 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2607.07207.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
28 of 28 outbound references displayed
- verified exact3
- verified fuzzy18
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation da3e8dda-7bc6-4a93-992e-7561add81ea0 · outbound
This paper cites an unresolved cited work.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Unresolved cited work
Reference 1
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T17:46:25.964576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8a55cafe-bc23-4ec6-91a0-22cbf7a04cdc · outbound
This paper cites an unresolved cited work.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T17:46:25.959120Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 20d7f733-86d5-422e-b2b9-ff0eb93c5c73 · outbound
This paper cites VentureBeat: https://venturebeat.com/technology/z-ais-open-weights-glm-5-2-beats-gpt-5-5-on- multiple-long-horizon-coding-benchmarks-for-1-6th-the-cost ; N.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency VentureBeat: https://venturebeat.com/technology/z-ais-open-weights-glm-5-2-beats-gpt-5-5-on- multiple-long-horizon-coding-benchmarks-for-1-6th-the-cost ; N
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.961017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a5fa9531-a057-49af-ba42-d4e4c5e04267 · outbound
This paper cites TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate
Reference 4
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T17:46:25.914347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 14836cd1-fdd4-45ae-b851-e8918c5b64ee · outbound
This paper cites CNBC, July 1–2, 2026: https://www.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency CNBC, July 1–2, 2026: https://www
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.967801Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 94521dca-2bec-48d6-8513-4849215ad3d7 · outbound
This paper cites CNBC, July 1, 2026:https://www.cnbc.com/2026/07/01/meta-stock-cloud-ai-compute.html.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency CNBC, July 1, 2026:https://www.cnbc.com/2026/07/01/meta-stock-cloud-ai-compute.html
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.954918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c5a96df4-6d1d-4d71-9724-6c9e57873623 · outbound
This paper cites https://www.softwareseni.com/understanding-the-2025- dram-shortage-and-its-impact-on-cloud-infrastructure-costs/.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency https://www.softwareseni.com/understanding-the-2025- dram-shortage-and-its-impact-on-cloud-infrastructure-costs/
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.962895Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e1a82693-e90f-4141-89f0-ecc19601b941 · outbound
This paper cites Decoding the Agentic Economy.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Decoding the Agentic Economy
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.966182Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 02f45900-deb2-4430-bb39-292b90ffc4d5 · outbound
This paper cites https://hai.
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.969390Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1328f2cb-232b-4a9b-928c-309a397a6608 · outbound
This paper cites https://a16z.
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.950832Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b92dda6f-b140-4fd2-89be-42cbc7dec686 · outbound
This paper cites https://openrouter.
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.949150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7e086e2a-5d1e-4a25-a188-53b6d88cd660 · outbound
This paper cites Pichai, Google I/O 2026 keynote (May 20, 2026): 3.2 quadrillion tokens/month, 7 × YoY; trajectory from 9.7T (2024) and 480T (2025).
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Pichai, Google I/O 2026 keynote (May 20, 2026): 3.2 quadrillion tokens/month, 7 × YoY; trajectory from 9.7T (2024) and 480T (2025)
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.947298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 088cb761-f377-437a-b4e3-fb864fd42c03 · outbound
This paper cites Summarized in https://www.uncoveralpha.com/p/why-token-optimization-is- a-gift.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Summarized in https://www.uncoveralpha.com/p/why-token-optimization-is- a-gift
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.945551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9f34a36a-ec52-40ab-8d01-c0a51da12c7b · outbound
This paper cites an unresolved cited work.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Unresolved cited work
Reference 14
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T17:46:25.981771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 728f79d0-b119-4245-9bb6-ec480724a461 · outbound
This paper cites LineShine Debuts at No. 1,.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency LineShine Debuts at No. 1,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.974871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e90e6459-0ce1-49a2-8e2c-4740951bedf8 · outbound
This paper cites A Deep Dive On China’s LineShine All-CPU, Exaflops-Class Supercomputer,.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency A Deep Dive On China’s LineShine All-CPU, Exaflops-Class Supercomputer,
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-07-09T17:46:25.908617Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0eb08cd4-124c-4143-bd48-6d3bc6cdfd45 · outbound
This paper cites Do We Still Need GPUs? Rethinking AI and Scientific Com- puting on Future CPUs,.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Do We Still Need GPUs? Rethinking AI and Scientific Com- puting on Future CPUs,
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-07-09T17:46:25.917032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 24af18d3-8e20-49ef-8355-435d83b80483 · outbound
This paper cites Do We Still Need GPUs? Rethinking AI and Scientific Computing on Matrix-Enhanced CPUs,.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Do We Still Need GPUs? Rethinking AI and Scientific Computing on Matrix-Enhanced CPUs,
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-07-09T17:46:25.920470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 52f6015e-2ed2-4769-b1af-f77e3107fb6c · outbound
This paper cites https://alatirok.com/ ai-circular-financing-explained/ ; https://tech-ish.com/2026/02/03/nvidia-openai- oracle-circular-financing-loop/.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency https://alatirok.com/ ai-circular-financing-explained/ ; https://tech-ish.com/2026/02/03/nvidia-openai- oracle-circular-financing-loop/
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.973150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9fb867ed-f3bd-42fe-9b02-6b536024ef84 · outbound
This paper cites Analysis: https:// intuitionlabs.ai/articles/oracle-openai-300b-deal-analysis.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Analysis: https:// intuitionlabs.ai/articles/oracle-openai-300b-deal-analysis
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.971223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 93232df3-50a6-408f-9767-887b31e7636c · outbound
This paper cites an unresolved cited work.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Unresolved cited work
Reference 21
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T17:46:25.978351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8b6afd80-3f54-4e93-bb85-ad6a79bcf663 · outbound
This paper cites Japan’s an AI Laggard. That Could Be Its Edge,.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Japan’s an AI Laggard. That Could Be Its Edge,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.976648Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b6f8fe94-61d2-4466-b782-c4fefd249e69 · outbound
This paper cites an unresolved cited work.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Unresolved cited work
Reference 23
- Resolution
- unresolved
- raw_fallback, observed 2026-07-09T17:46:25.980125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a07932a6-232d-4429-aa4a-84992a846b54 · outbound
This paper cites https://www.nvidia.com/en-us/products/ workstations/dgx-spark/.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency https://www.nvidia.com/en-us/products/ workstations/dgx-spark/
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.985598Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2d2378bb-499d-4d35-aeb4-d90dac5b4057 · outbound
This paper cites PYM- NTS, May 2026: https://www.pymnts.com/news/artificial-intelligence/2026/token-shock- hits-silicon-valleys-biggest-spenders/.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency PYM- NTS, May 2026: https://www.pymnts.com/news/artificial-intelligence/2026/token-shock- hits-silicon-valleys-biggest-spenders/
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.983566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 622f1d98-ba3c-4336-b4eb-f2dcad6a782a · outbound
This paper cites Beyond Per-Token Pricing: A Concurrency-Aware Methodology for LLM Infrastructure Cost Estimation.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Beyond Per-Token Pricing: A Concurrency-Aware Methodology for LLM Infrastructure Cost Estimation
Reference 26
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T17:46:25.911640Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 8f81f376-55e1-43a2-b341-3da6b1c7f0e7 · outbound
This paper cites Via Business Insider: https://uk.finance.yahoo.com/news/ ubs-says-majority-enterprise-companies-090701077.html.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency Via Business Insider: https://uk.finance.yahoo.com/news/ ubs-says-majority-enterprise-companies-090701077.html
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.957403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2bfc8393-ade1-42e2-bf29-44f2709a84d6 · outbound
This paper cites https://www.anthropic.com/news/claude-fable-5-mythos-5 ; context: https://www.bloomberg.com/professional/insights/markets/ai-boom-built-on- shaky-geopolitical-footing/ 22.
Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvency https://www.anthropic.com/news/claude-fable-5-mythos-5 ; context: https://www.bloomberg.com/professional/insights/markets/ai-boom-built-on- shaky-geopolitical-footing/ 22
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-07-09T17:46:25.953020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Pith citing papers
No inbound Pith citation observations are available.