🇺🇸🤖 Hardware and autonomy stacks all over the US robotics map (via @MFGMillennial / MFGMIL). The missing box is the “data human‑in‑the‑loop” layer for Physical AI: egocentric video, teleops, real‑world ops. That’s where Remotics plugs in.

🤖 Physical AI doesn’t learn only from polished demos. 🎥 Egocentric video connects everyday work with how robots learn: – the person doing their job – the same scene from their own first‑person view At Remotics, we turn this into training data for robots in real operations. #EgocentricVideo #PhysicalAI #HumanInTheLoop #Teleoperations #Robotics

On May 26th in São Paulo, @SergioOliv15922 joined a small “Connecting the Americas” session on how AI‑powered services are reshaping business between Brazil and the US. 🌎 The most valuable conversations often happen off‑stage with people who are already building. #PhysicalAI #robotics

🤖 The robotics industry is learning that models alone are not enough — high‑quality human data is becoming core to Physical AI. 🎥 This clip shows a new way to use egocentric video from real hands and real tasks so robots learn from the actual mess of production lines. ⚙️ By combining egocentric and teleops data, teams can design, train and validate robots that adapt faster and fail less in the real world. #PhysicalAI #EgocentricData #Robotics #Humanoids

🤖 Egocentric video is how you stop training robots only on clean demos and start training them on how humans actually work. 🌎 At Remotics we design and capture egocentric video teleops data from real operations in Latin America, so Physical AI teams get the human demonstrations their models really need. #EgocentricData #PhysicalAI #Robotics #Teleops #LatAm

Most “ #teleoperation centers” are just people behind screens. The teams that keep #robots in service at scale usually invest in 3 things: 1️⃣ Operational maturity 2️⃣ Data mindset 3️⃣ Nearshoring & reliability This is the layer we’ve been building at Remotics: human infra data for #PhysicalAI

Day 2 at #roboticssummit Key insight from conversations: teleoperation data is emerging as the highest-quality input for training Physical AI models. Why? It's generated during real-world robot operations — companies can improve models while scaling simultaneously. 540K hours of teleoperation = valuable training data. #RoboticsSummit #PhysicalAI

We’re heading to @RoboticsSummit in Boston next week, May 27–28. If you’re scaling #robots and want to discuss how nearshored teleoperation can help reduce operational overhead, our President & CGO, Sergio Oliveira, still has a few meeting slots available. Book: calendly.com/sergio-remotics… #RoboticsSummit #Robotics #Teleoperation

Everyone in robotics is chasing full autonomy. After 540,000 robot operation hours, here's what we've learned: The bottleneck isn't better AI models. It's operational infrastructure. 🔧 Remote supervision is continuous, not occasional ⚙️ Exception handling scales with fleet size 💰 Unit economics depend on cost-per-task, not autonomy % The companies scaling today deploy hybrid systems: AI expert human operators. That's the unlock. #PhysicalAI #Robotics #Teleoperation #Automation #AI

Whole-body coordination for heavy objects is one of the toughest challenges in robotics. Atlas nailed it. 🤖 Now imagine scaling this across thousands of operations—that's where the real data challenge begins.

The world's first production-ready manned mecha. Systems like these generate massive operational data. That's where we come in—at scale. 🤖

Unitree Unveils: GD01, A Manned Transformable Mecha, from $650,000 👏 The world's first production-ready manned mecha. It can transform. It's a civilian vehicle. It weighs ~500kg with you inside. Please everyone be sure to use the robot in a Friendly and Safe manner.