Kai Williams writes:

Just last week, at the 2026 World Humanoid Robot Games in Beijing, a robot ran 100 meters in 8.86 seconds, crushing Usain Bolt’s human world record of 9.59 seconds. At last year’s competition, the fastest robot took more than 20 seconds to run 100 meters.

Demonstrations like these have impressed a lot of casual observers — and created a lot of anxiety about future job losses. If humanoid robots can already serve people drinks, perform elaborate dance routines, and outrun humans, how long will it be before they put millions of people out of work?

But if you talk to robotics experts — and I’ve talked to many in recent months — a more nuanced picture emerges.

As Physical Intelligence co-founder Karol Hausman put it, people (including himself) “are not very good at judging progress in robotics or judging what is impressive and what isn’t.” Sure, robots can do acrobatic maneuvers that are “very difficult for a human to do,” he said. But then “something as simple as picking up a Coke can turns out to be very, very difficult.”

Some of the most impressive demos of humanoid robots involve someone controlling the robot remotely — a process known as teleoperation. It seems pretty clear this was the case with those Optimus robots in 2024, for example. Tesla’s hardware was sufficient to act as a bartender, but its software wasn’t up to the task. So Tesla apparently hired human operators to control the robots remotely.

And while those Unitree robots’ dance moves were not teleoperated, they don’t tell us all that much about the robots’ capacity to do useful work. Most physical labor involves manipulating objects in the real world — packing boxes, hammering nails, flipping hamburgers, and so forth. As we’ll see, training a robot on physical manipulation tasks like these is much harder than training a robot to dance.

There are also broader challenges that transcend individual tasks. For example, human workers are extremely flexible — they can perform a wide variety of tasks, and they can learn easily while on the job. So far, nobody has figured out how to give AI robotics models the same capacity for generalization. [Continue reading…]