Title: Synthetic Data Generation for Data Sharing: A Case Study, Speaker: Dr Thomas Ingram | The Christabel Pankhurst Institute
Title: Synthetic Data Generation for Data Sharing: A Case Study, Speaker: Dr Thomas Ingram | The Christabel Pankhurst Institute
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Training data collection is one of the biggest challenges in #Robotics. We're solving it with #NVIDIAIsaac GR00T-Dreams. By using #NVIDIACosmos world foundation models and generative AI, developers can create vast, realistic synthetic data at scale. Benefits: ✔️Cheaper & faster data collection ✔️Smarter robots in new environments ✔️ No more teleoperation bottlenecks ✔️ Small teams = massive impact Get Started 🔗 https://nvda.ws/3G4Ggcx #GTCParis #VivaTech | NVIDIA Robotics
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Here’s the secret to synthetic data. 👀 The teams using it to solve really hard real-world problems… aren’t eager to tell anyone how good it actually is. At SPIE Photonics West, I shared one of my favorite examples. A team trained seven models using 100% synthetic data physics-based. Then then they tested those models in real apple orchards. Result? 🍎 34% higher accuracy than models trained on the open-source real-world apple dataset. Why does this work? Because synthetic data lets you aim exac
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How do qual researchers feel about the opportunities and threats of synthetic data? Synthetic audiences are suddenly everywhere. The promise is obvious: faster, cheaper, easier. But the risks are… | Hugh Carling | 22 comments
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