😴 Tired of delayed deliveries? Here's how AI is making "out for delivery" actually mean something:
Picture this: Warehouses full of workers, sorting packages by hand. Repetitive. Exhausting. Accident-prone. Now, imagine robots doing that job - faster, safer, 24/7. That's already happening. 🤕 ➡ 🤖 😃
But here's the kicker: Those robots 🤖 ? They're about to get a major upgrade.
🏃♂��� 🏃♀️ UPS, FedEx, and other logistics giants are racing to implement next-gen vision systems. The goal? Robots that can instantly recognize and sort ANY package, no matter how weird or wonky.
The problem? Training these systems is SLOW. Like, "we'll-get-back-to-you-next-year" slow. ⏱ 🐢
Enter Advex. Our secret sauce? We don't wait for real-world data. We CREATE it. Thousands of synthetic images, covering every possible package scenario you can imagine (and some you can't). 🎨 📦
The result? A major logistics provider used Advex to supercharge their system's accuracy by 33% - in just 12 hours. ⏱ 🐇
Honored by the kind words from @brandontrabucco! Brandon's DA-Fusion paper at ICLR'24 broke new ground in diffusion-based synthetic images for CV model training.
We're pushing the boundaries of this tech, and we're growing our team to do even more. Join us:
Diffusion Researchers: https://t.co/pErYTjiczL
Machine Learning Engineers: https://t.co/kDX5v6nHJN
Unlock the Power of Synthetic Data in Computer/Machine Vision 🔐
🚀 With AI vision blowing up in manufacturing and robotics, you have many options for vision system hardware and software 📸
Nevertheless, researchers agree that the data you use to train these systems is actually the most important ingredient 👨���🍳 📈
Having on demand and high quality synthetic data allows you to:
🔷 Instantly create balanced, diverse datasets
🔷 Accelerate development and deployment
🔷 Boost model performance
🔷 Quickly address model drift
Learn more at https://t.co/xI0UGAqEUO.
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