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Wikimedia

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Headlines · 3

  1. Hallmark cuts AI-style landing page clichés, but sharply raises build time

    In a self-reported same-brief test using Claude Code with Sonnet 5.5, Hallmark eliminated all-caps labels above headings and replaced two empty image placeholders with credited Wikimedia photos. The build took 3 minutes 32 seconds with Hallmark versus 44 seconds without it, while agent turns rose from 2 to 30. The author also reported that Hallmark’s audit found 21 issues on a plain page but applied its own stylistic rules, while mobile checks required Chrome and puppeteer-core.

    r/ClaudeAI · 🔥 0
  2. AI models help uncover chained PHP2Shell remote-code-execution flaws

    O’Reilly Radar, citing Wiz Research, reports that Wiz Atlas, Gemini 4 Argon and GPT-5.6 Sol helped uncover two chained PHP remote-code-execution vulnerabilities, later identified as CVE-2026-109618 and CVE-2026-109619. The PHP Foundation released PHP 8.5.12, 8.4.27, 8.3.36 and 8.2.35 and urged all installations to update, while sites unable to upgrade were advised to go offline and be isolated. The reported timeline also says Amazon apparently detected exploitation before the vulnerabilities were prematurely disclosed and patched.

    O’Reilly Radar · 🔥 0
  3. AI translation is fluent now, but human checkers remain essential

    BBC reports that Google says people now translate one trillion words a month with Google Translate, while direct sales of machine translation outside general AI subscriptions were estimated at $1.4bn last year. OKA (Open Knowledge Association), a Swiss non-profit, ran a Wikimedia-funded study covering 119 articles, 10 language pairs and more than 1,000 hours of translator work, finding that 27% of AI-generated text was still corrected before publication, three-quarters of those corrections were errors the AI introduced, and 5 to 6% of errors changed the meaning of the original. Legal and medical translators cite AI rendering "Le demandeur" (the plaintiff) as "the requester" and translating the Greek letter μ as milli rather than micro, a thousandfold dosage error; CNRS researcher François Yvon says the way these systems function makes 100% reliability hard to imagine.

    BBC Technology · 🔥 0

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