Artem Voloskovets
⬤ Agibot Research just rolled out its Scalable Online Post-training (SOP) system—a breakthrough that lets robots get smarter by streaming their real-world experiences and human feedback straight to a cloud platform. Instead of learning once and calling it done, these robots keep getting better through continuous cloud updates, picking up new skills way faster than before.
⬤ What makes SOP special is how it crushes traditional offline training methods. The system learns in real-time, which means it's way more efficient. Here's the cool part: when you add more robots to the fleet, performance scales almost linearly—basically, more robots equals faster learning for everyone. They're already nailing tricky tasks like folding different types of cloth and restocking grocery shelves, where understanding physical properties and context really matters.
⬤ The real magic happens with Vision-Language-Action models—the brain behind how robots make decisions and execute tasks. SOP's continuous feedback loop supercharges these models, letting robots adapt their skills on the fly across different real-world situations. When robots share what they've learned with each other, they get better at tons of tasks without needing someone to program every single move.
⬤ This could be huge for automation across industries. Imagine robots that actually learn and improve while they work—businesses get more done, cut labor costs, and can roll out robotic solutions faster in factories and warehouses. Since SOP scales so efficiently, any industry dealing with repetitive tasks could see massive productivity gains while building a smarter, more independent robotic workforce.
Artem Voloskovets
