Physical AI и VLA-модели: гонка гуманоидов между Китаем и США, и что есть у России

In July 2026, the blog of the company BotHub on Habr published the second part of a major deep dive into PhysicalAI — the "physical intelligence" of robots. The first part explained the technology, while the second is devoted to economics, industrial adoption, government programs, and the race between China and the US for humanoids.

What the second part of the deep dive covers

The second part focuses on how "physical intelligence" lives in reality — in the economy, in production, and in government strategies, not only in research labs. The authors move from theory to practice: who is spending money on what, where robots are already working, and which countries are setting the pace.

• The economics of humanoid robots and the cost of adoption
• Industrial application of VLA models in real production
• Government programs supporting robotics in China and the US
• Russia's place in the "physical intelligence" race
• The human factor: how people accept robots

The key question of the whole series is whether "physical intelligence" can repeat, in the world of atoms, the leap that generative models have already made in the world of bits.

Why has classical robotics hit a ceiling?

Classical robotics has hit a ceiling because of rigid programming: a traditional industrial robot performs a pre-scripted sequence of movements and cannot adapt to an unfamiliar environment. Change a part, the lighting, or the position of an object, and the script breaks.

The breakthrough the deep dive talks about is VLA models (Vision-Language-Action): an architecture where the robot gains the ability to generalize from large language and vision models. It doesn't just repeat a memorized movement — it "understands" the task in natural language and transfers the skill to new situations.

"Classical robotics hit a ceiling, and language models turned into VLA," is how the authors of the deep dive on

BotHub's blog on Habr formulate the key shift in the industry.

The race between China and the US for humanoids

The race for humanoid robots is led primarily by two countries — China and the US — whose government programs and industrial ecosystems the deep dive examines in the most detail. Both are betting on "physical intelligence" as the next big technological wave after generative AI.

The bet specifically on a humanoid form is explained simply: the world around us — factories, warehouses, homes — is designed for humans, so a humanoid robot can work in the same places as people, without rebuilding the infrastructure.

A separate storyline in the second part is what Russia has in all this: what developments, teams, and groundwork exist, and how realistic it is to join a race where the leaders have already invested significant resources. The authors honestly examine the economics, the industry, and human nature — why robot adoption runs up against more than just technology.

What this means

PhysicalAI is moving out of the stage of lab demonstrations into the realm of economics and government strategy: humanoids and VLA models are becoming a subject of industrial competition between China and the US, and the question for Russia is whether it can secure its own place in this race in time. For business, this is a signal: robotics is ceasing to be a niche for engineers and turning into a field where capital, production capacity, and government support are what decide the outcome.

Frequently asked questions

What is a VLA model?

VLA (Vision-Language-Action) is a class of models that combine vision, language, and action: the robot perceives its surroundings through cameras, understands the task in natural language, and builds its own sequence of movements. This approach has replaced the rigidly programmed scripts of classical robotics.

What is PhysicalAI?

PhysicalAI, or "physical intelligence," is the transfer of the capabilities of large AI models from the digital world into the physical one: robots and humanoids that act in a real environment. It is exactly this — along with its economics, industry, and government programs — that the deep dive on Habr is devoted to.