#Metaverse
HMS, http://
frontline.io Unveil Enterprise AR Headset at Tokyo XR
TECHNOLOGY
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HMS and Frontline Unveil Enterprise AR Headset at Tokyo XR
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Signs of accelerating technological progress emerging
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If this isn’t a sign that things are speeding up, I don’t know what is
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Deep Learning Revolutionizes Marketing Measurement Systems
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Why is this hard? Because most of the tools we use to measure marketing were built on math from the 1970s. Meanwhile, other industries — like weather, drug discovery, and finance — are using supercomputing and deep learning to model complex systems. Puig asks: Why not
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Software Evolution: From Code to AI Prompting Era
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The best 30 minutes you’ll spend this week.@karpathy breaks down "Software in the Era of AI" at Y Combinator:
— Charly Wargnier (@DataChaz) 3 juillet 2025
from Software 1.0 (code you write), to 2.0 (code you train), to 3.0 (code you prompt).
Full talk in 🧵↓ pic.twitter.com/DkgmWzuYOIThe best 30 minutes you’ll spend this week. @karpathy breaks down "Software in the Era of AI" at Y Combinator: from Software 1.0 (code you write), to 2.0 (code you train), to 3.0 (code you prompt). Full talk in ↓
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Tour de France 2025 Uses AI and IoT for Enhanced Experiences
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Tour de France 2025 Tech is awesome! Digital tools, including #AI and #IoT sensors, are set once again to help fuel rider and fan experiences at the race… "The bikes themselves have become something of a data hub." https://
iotworldtoday.com/connectivity/t
our-de-france-2025-tech-enhances-rider-fan-experience
… #EdgeComputing #5G #DataDriven -
Bring Back the Golden Timeline of Daily Industry Reinvention
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we had a 6 month golden-timeline where every day you saw someone reinventing industry. bring that back please
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Significant performance improvements made to Tab model
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And made significant performance improvements to our Tab model.
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Tech Industry Lacks Inspiration Amid Reality TV Culture
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the technology industry feels like reality tv right now. i guess it's fun to watch but it's really deeply uninspiring
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PyTorch NumPy Implementation Code Repository Released
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here's where the code lives: https://
github.com/pytorch/pytorc
h/tree/main/torch/_numpy
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LLM Pretraining Evolution: From Crisis to Solved Problem
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two or three years ago, this was a prevailing sentiment “training the largest LLMs is very hard. only a few people know how. everyone else is failing” it was hard to avoid huge loss spikes. now pretraining is a solved problem. what changed? do we just clean our data better?