Humanoid says KinetIQ Ascend reinforcement learning approaches human-level dexterity - The Robot Report
Humanoid is building humanoid robots with the goal of becoming the No. 1 general-purpose industrial humanoid robotics company within two years. Founded by Artem Sokolov in 2024, it has more than 250 engineers, researchers, and innovators from top global tec...
Key takeaways
- The humanoid‑robot market is accelerating worldwide, with several high‑profile launches and investments reported in July 2026.
- In China, UBTECH and Unitree Robotics have both opened new facilities in Tianjin’s Economic‑Technological Development Area, creating a closed‑loop production line that spans R&D, manufacturing and after‑sales support and positioning the country to dominate over 90 % of global shipments.
- In the United States, Apptronik has expanded its Austin “Robot Park” to collect data and train Apollo humanoids in partnership with Google DeepMind, while AGIBOT announced the European debut of its A3 humanoid and a Robot‑as‑a‑Service model in the UK, and celebrated the rollout of its 15,000th robot, the G2 industrial‑grade unit.
- The London‑based startup Humanoid introduced its KinetIQ Ascend reinforcement‑learning system, claiming 99.9 % manipulation reliability at human speed and demonstrating scalable performance across single‑arm and bimanual tasks.
- Meanwhile, former Tesla engineer Rémi Cadène’s Paris startup UMA unveiled a lightweight humanoid called Northstar, featuring a “real‑time learning” architecture that lets the robot acquire new skills from demonstration, and is already in talks with about 50 potential customers for manufacturing, logistics and home use.
Humanoid is building humanoid robots with the goal of becoming the No. 1 general-purpose industrial humanoid robotics company within two years. Founded by Artem Sokolov in 2024, it has more than 250 engineers, researchers, and innovators from top global tech companies.
With offices in London, Boston, Vancouver, and San Diego, Humanoid said it is building commercially viable, scalable, and safe systems for real-world applications. In May, the company partnered with Bosch and Schaeffler to scale production of its HMND robots.
KinetIQ Ascend supports ‘capability factory’ The Robot Report
Humanoid says KinetIQ Ascend reinforcement learning approaches human-level dexterity
By The Robot Report Staff |
Arm drift after long reinforcement training caused by action prefix drift. Source: Humanoid
Robotic manipulation is making progress with artificial intelligence. London-based Humanoid last week introduced KinetIQ Ascend, its reinforcement learning, or RL, approach designed to reach 99.9% manipulation reliability at human speed and beyond.
“The humanoid race is becoming a question of scale, and real-world RL can be a core part of the answer,” stated Jarad Cannon, chief technology officer at Humanoid. “Robots that once required months of manual tuning are now outperforming human demonstrations within days.” Humanoid said the results demonstrated that KinetIQ Ascend shows a new way of developing robot capabilities, proving effective across a range of real-world operational tasks, from high-speed single-arm picking to complex bimanual handling.
KinetIQ Ascend also demonstrated that robot performance improves predictably as training time increases. It’s similar to how large language models (LLMs) improve as more compute and data become available. The company said that the observed scaling trend, supported by simulation experiments, suggests that its method scales all the way to 100% reliability.
New robots, funding, and signals. Every Thursday.
Unsubscribe anytime.
Mentioned in this article