Robots built for real workplaces need more than capable AI models. They need a seamless path from data to deployment and reliable performance amid changing materials, equipment constraints, and exceptions. Genie Studio 2.0 brings the full embodied AI lifecycle together in one platform.From data collection and model training to simulation, evaluation, deployment, task orchestration, and fleet operations, new tasks can reach deployment validation in as little as seven days. Discover more： #AGIBOT# #GenieStudio# #EmbodiedAI# #Robotics#

Robots Never Clock Out | AGIBOT G2’s 24-Hour Convenience Store Challenge Six AGIBOT G2 take on a 24-hour shift as convenience store trainees. From rush-hour crowds to late-night solo duty and the morning breakfast sprint, can they keep up with nonstop customers and unexpected requests?

Robots Never Clock Out | AGIBOT G2’s 24-Hour Convenience Store Challenge Six AGIBOT G2 take on a 24-hour shift as convenience store trainees. From rush-hour crowds to late-night solo duty and the morning breakfast sprint, can they keep up with nonstop customers and unexpected requests? Stay tuned for the live stream! ⏰Nov 2, 10:00 AM – Nov 3, 10:00 AM (UTC+8)

robots.txt has been around since the 90's, but it took until 2022 for it to become an official internet standard. Nearly 30 years of websites politely asking robots not to wander into certain places. And now some of us are using the same system to try to keep AI crawlers out. 😂

Robots have their own KPI now? At AGIBOT Innovation Day 2026, co-founder Peng Zhihui said: “From today on, we hope that when the industry talks about the value of robots, it won’t just be about specs and demos, but how many effective hours of intelligent work they’ve actually delivered.” AGIBOT calls this new metric Worken: active robots × autonomous working hours × output efficiency ratio.

Robots at Dexory are being continuously tested 🔁 Over and over again :-) I asked Andrei Danescu about testing, and that was the answer. Which is the thing simulation cannot touch. You can simulate perception, dynamics, contact, a whole snowstorm. You cannot simulate twelve months of bearing wear, cable flex, thermal cycling and dust. Reliability data arrives at one second per second. Here's the YouTube video from my visit in their factory (subscribe if you like robots hehe):

Robots are everywhere at trade shows, but few make it from the lab to deployment at scale. @Intel’s John Healy explains how Physical AI Studio, OpenVINO, and an open approach to hardware and software help close the “deployment gap” by reducing technical complexity and keeping TCO sustainable. $INTC