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Snap’s new partnerships with Salesforce, AWS, Nvidia and specialist software firms shift its $2,195 Specs glasses away from a vague consumer replacement for the phone. The more credible pitch is hands-free guidance for field, retail and remote-support work—where the price has to earn its keep.
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Mercedes did not invent a miracle call to win in Madrid. Its latest account of Kimi Antonelli's Virtual Safety Car stop shows the real advantage: rehearsed decisions, a driver already in the window and a pit crew ready before the opportunity became obvious.
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Microsoft has put a draft Humanist AI Code of Conduct out for public comment, proposing that its future MAI models remain subordinate to people, accept correction and stay within authorized scope. That is a useful line in the sand—but the company is not using the document to train models yet.
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Google has agreed to buy environmental attribute certificates linked to up to 91,000 tonnes of Stegra’s first-year steel output in Sweden. It is a more specific kind of climate procurement than a data-centre slogan—and a useful test of whether certificate markets can help expensive industrial projects reach commercial scale.
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Google Labs has turned its CC daily-brief experiment into a shared household agent for up to six people. The appeal is obvious: calendars, school notices and forms in one place. So is the harder question—whether a household can maintain sensible consent when one agent is invited into everybody’s data.
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Alpine has hired former Mercedes technical chief Mike Elliott to oversee its technical and engineering operation at Enstone. The significance is not a borrowed CV: it is a clearer line of accountability as a promising Mercedes-powered reset tries to become a repeatable front-running project.
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Apple’s new “What Holds Us” show is promotional, but it is still a better way to judge the iPhone 18 Pro camera’s new variable aperture than another lifestyle montage: three photographers had to make it work across mountains, a studio, and a crowd scene.
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A new alliance led by Emerald AI, Google and NVIDIA wants data centers to vary their power draw when the grid is under strain. That is a sensible direction for AI infrastructure, but it is a promise that will need measured response data—not coalition membership—to earn public confidence.
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Vera Rubin NVL72’s first MLPerf inference numbers are a useful signal, not a buying guide: the preview results point to a rack-level race in which software, networking and workload choice matter as much as the accelerators inside.
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