Author: Rinat Mirzaitov

The humanoid robotics race has a new class of competitor. For the past several years, the industry has largely been framed as a contest between companies building robot bodies, actuators, hands, control systems and manufacturing capacity. Now two of the most powerful frontier AI laboratories are moving directly into the physical layer, but they are approaching it from very different directions. OpenAI CEO Sam Altman made the clearest declaration yet in a September 1 interview with Alex Heath. Asked whether OpenAI was building a humanoid robot, Altman replied: “We will definitely do a humanoid.” He added that OpenAI expects to…

Anthropic’s August 27, 2026 research preview of the Model Hardware Standard, or MHS, puts a useful question in front of the robotics industry: how much of Physical AI’s difficulty comes from intelligence itself, and how much comes from the fact that every machine exposes the physical world differently? MHS proposes a shared driver layer that lets AI agents discover programmable devices, inspect their state and capabilities, and operate them through common primitives such as read and write. Anthropic says device descriptions can also expose characteristics and enforced safety limits. Universal Robots subsequently said it tested the preview on four cobots,…

Humanoid robotics has an unusually important characteristic for startups: many of the industry’s biggest problems are not confined to the companies building complete robots. They sit underneath them. Actuators remain expensive and difficult to scale. Dexterous hands still struggle with the combination of strength, compactness, sensing, and reliability. Robot learning requires large amounts of physical-world data. Safety requirements become harder when robots leave cages and work around people. Factories still need robots connected to existing equipment, software, networks, and production processes. Once deployed, somebody also has to measure reliability, diagnose failures, recover from exceptions, and keep fleets productive. That creates…

Smart Analytics Global (SAG) estimates that 19,100 humanoid robots shipped worldwide in the first half of 2026, up 272% from 5,100 a year earlier. AGIBOT accounted for approximately 8,400 units, Unitree 5,900, Galbot 900, UBTECH 700 and Leju 600. AGIBOT and Unitree alone represented about 75% of reported shipments. Those numbers are significant. They show an industry moving from prototypes toward manufacturing volume. But they do not answer the more commercially important question: Where are those robots actually working? That question matters because a robot can be produced, sold, shipped, delivered, accepted and operated at different points in its commercial…

Humanoid robotics is usually framed as a race among companies building complete robots. Humanoid Analytics’ July 2026 market snapshot shows a broader competitive structure. Of 351 tracked Core and Adjacent entities, 225 are core humanoid builders or substantial corporate programs. Another 126 sit in Adjacent segments including dexterous manipulation, sensing, components, AI, data infrastructure and system integration. Adjacent companies therefore represent 35.9% of the tracked Core and Adjacent universe. That number is the useful finding. It is not market share. It does not measure revenue, adoption, maturity, technical quality or market value. It shows that more than one-third of the…

Humanoid robotics may never have a single ChatGPT moment. That would not mean the industry failed. A more plausible outcome is that humanoids become commercially important through a sequence of narrower breakthroughs: one task becomes economical, one customer expands, one robot learns a second workflow faster, service requirements fall, production rises, and another deployment becomes easier because of what was learned from the first. For investors, this would produce a very different market from the one implied by waiting for a single foundation-model release that suddenly makes humanoid robots broadly useful. The key question would shift from when the breakthrough…

Humanoid robotics is difficult for a reason that is easy to underestimate from demonstration videos: the robot has to solve many problems at the same time. It must perceive its surroundings, understand a task, decide what to do, move through physical space, maintain balance, manipulate objects, respond to unexpected conditions and monitor its own hardware. Those functions must work together quickly enough for the machine to remain useful and safe. That makes a humanoid fundamentally different from an AI system that only produces information on a screen. A humanoid converts intelligence into physical action, and every action creates new information…

The technological story through 2035 is unlikely to be one sudden moment when artificial intelligence overturns the economy and humanoid robots immediately replace large categories of physical labor. The more credible forecast is both slower and more consequential: technological capability will continue advancing rapidly, while companies, institutions and physical infrastructure absorb those capabilities at a much slower rate. ChatGPT was released publicly on November 30, 2022, not 2023, although 2023 was the year generative AI became a mainstream business and investment question. The distinction matters because more than three years later, the gap between what AI systems can technically do…

The hardest problem facing humanoid robotics companies is no longer simply making a robot walk, manipulate an object, or complete a carefully selected task. It is converting those capabilities into customer operations that work reliably, safely, repeatedly, and economically enough to survive procurement, integration, and renewal. Public evidence now establishes that useful humanoid work is possible. BMW has confirmed substantial operating activity involving Figure 02, while GXO has confirmed a commercial deployment of Agility Robotics’ Digit. These are material advances beyond promotional demonstrations. They do not yet establish that humanoid robots can be deployed broadly, supported cheaply, or operated profitably…

The Federal Communications Commission has created a formal U.S. market-access barrier for foreign-produced advanced robots just as Unitree Technology prepares to open subscriptions for its Shanghai STAR Market IPO. The strongest evidence is an FCC public notice issued July 28 and Unitree’s own risk disclosure reported by Reuters. The restriction applies to new covered equipment authorizations, while previously authorized Unitree products are not automatically removed from sale. The main uncertainty is how much the policy will constrain future models rather than the company’s existing U.S. business. The FCC added “foreign-produced advanced robotic devices” to its Covered List following an interagency…