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Data Center News > Blog > AI > Time Magazine appears to accidentally publish embargoed story confirming new Anthropic model
AI

Time Magazine appears to accidentally publish embargoed story confirming new Anthropic model

Last updated: May 25, 2025 10:14 am
Published May 25, 2025
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Time Magazine appears to accidentally publish embargoed story confirming new Anthropic model
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The San Francisco-based AI startup Anthropic had already knowledgeable most people that it deliberate to make an announcement immediately, Thursday, Could twenty second with a livestream scheduled for 9:30 am PT.

Many within the wider AI energy consumer neighborhood, particularly on X, started to theorize that the announcement would mark the launch of a new Claude model codenamed “Neptune,” primarily based on earlier inspection of Anthropic paperwork and code on-line, which some took to be a brand new model of its highly effective Claude giant language mannequin (LLM) household, doubtlessly the long-awaited “Claude Opus,” a larger-parameter (denoting extra inner settings and complexity) mannequin successor to the present Claude 3.7 Sonnet.

Now, it seems that Time Journal has unintentionally confirmed that rumor, publishing and rapidly eradicating an article on its web site, in line with the observations of eagle-eyed AI programmers and news bloggers on X.

Somebody additionally seems to have revealed a full scrape of the Time article online on the information aggregator app Newsbreak, although that too has now been taken offline.

The main focus of Time’s piece was on security dangers and mitigations, however it does reveal that the brand new Claude is sensible sufficient to doubtlessly assist novices create new bioweapons.

There are scant specifics concerning the mannequin measurement, price, licensing phrases, and efficiency on generally used third-party AI benchmarks. For these, we are going to simply have to attend till extra data is revealed by Anthropic — or leaked by members of the press and AI neighborhood.

See also  Scaling smarter: How enterprise IT teams can right-size their compute for AI

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