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Zandvoort incoming. The New Money App already in pole position.
Cecilia Zandalasini (18 PTS) and the @valkyries defeat the Lynx for the first time in franchise history 😤
P9 at Zandvoort. Highest finish of the season, and points on the board. Congrats, @AstonMartinF1 💚 During Lap 30, the call was made to switch from softs to hards. On race day, over 40 live radio channels are monitored, transcribed, and compared in real time to help make that decision.
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The Formula 1 Zandvoort circuit dress lights up in real time based on the results of the Formula 1 Grand Prix. Tech fashion designer and IEEE Spectrum contributor Anouk Wipprecht explains how she created the technical design. #f1# #formula1# #grandPrix# #fashionDesign# #tech#
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Moody's Analytics Chief Economist Mark Zandi says Nvidia's earnings prove that the AI investment cycle is a "juggernaut" and critical to growth on on Balance of Power
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Scuderia Ferrari HP has arrived in Zandvoort! 🇳🇱 The weekend starts now and we’ll be part of every moment alongside our Official Partner @scuderiaferrari #VantageXScuderiaFerrariHP# #VantageMarkets# #ForzaFerrari# #F1#
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Momentum meets precision. @MercedesAMGF1 arrives at Zandvoort for the #DutchGP#.
Back within one 👀 Cecilia Zandalasini gets downhill off the closeout to make it a one-point game, 80-79. GSV-PHX | USA Network Tap to Watch:
TechCrunch reported that Encord is working with Zander Labs to test a new physical-AI data pipeline: capturing first-person video and brain-wave signals while humans perform manipulation tasks. This is not about “mind-controlled robots.” The goal is to make training data more informative. Brain signals could help mark intent, error, surprise or cognitive load — context that video alone may miss. Encord’s broader physical-AI data stack also includes in-field collection, teleoperation, multi-sensor data, annotation and deployment feedback. Robots need structured examples of hands, tools, objects, motion, timing and failure cases to learn the physical world.
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