This is the first piece in our new robotics series, and the goal is simple. Go one layer deeper than the hype without forcing you to get a PhD. I’m going to walk through the infrastructure that actually powers robots, both hardware and software. And surface the parts of the stack where progress is actually compounding.
I’m starting with dexterity and hands, because a robot would be a useless (and expensive) pile of metal if it couldn’t use its hands properly. It’s not just a hardware problem; it’s about a unique form of intelligence. Working on this research made me appreciate what a gift our hands truly are.
Let’s dive in!
-Teng Yan
Man is the wisest of all animals because he has hands.
I learned this watching my grandmother fold laundry.
She sat on the edge of the bed with a warm pile fresh from the dryer. Towel, shirt, socks, one after another. Her eyes were half closed, drifting in and out of a television show she had already seen a dozen times. Her hands never paused. Corners met cleanly. Sleeves tucked themselves in. Each piece landed in a neat stack, the same size as the last.
She was barely paying attention. The movements ran on their own. The skill had sunk below awareness, into something older and quieter. A kind of ancient intelligence, running on its own.
That is what human hands are. Not accessories, but a form of intelligence we barely notice. 400 million years of evolution compressed into a tool you can’t fully explain, even while you use it perfectly.
That is why robot demos often leave me with a faint sense of pity.
They can backflip flawlessly on demos, then struggle to load a dishwasher without teleoperation. They can run. They can jump. They still lose to dirty plates.
This piece is about why dexterity is a real bottleneck in robotics, why it lives below intelligence, and how to tell real progress from impressive demos.
We are looking for intelligence in the wrong place. For a long time, we inherited a bias that treated the body as a servant of the brain. Think first. Move second. In practice, the order is reversed.
As neuroscientist Daniel Wolpert argues, the real reason humans have such a powerful brain is to generate complex movement. The brain exists to control the body, not the other way around.
Try this. Reach out to touch the cheek of someone you love. Before contact, your hand reshapes itself to the curve of their face. At contact, force spreads across bones and tendons, skin floods your nervous system with signal, your grip adjusts without effort. The touch lands soft. You didn’t plan it. And you couldn’t describe it afterward.
To your mind, this feels like nothing. To a robot, it is everything.
Robotic manipulation is a fight with how much of reality lives at the point of contact. We are trying to force metal and plastic to reproduce a capability forged over hundreds of millions of years of evolution, and we often cannot even describe the skill we are trying to copy.
So before we talk about progress, we need a sharper definition of the problem.
What’s Dexterity?
Many confuse movement with dexterity. A robotic arm welding a car door is not dexterous. It is precise. It can repeat a pre-calculated path because it operates in a highly structured environment where every variable is controlled.
Dexterity is the ability to manage contact forces when the world does not cooperate.
It is rotating a pen in your fingers without dropping it.
It is the way your skin feels the edge of a coin in a dark pocket.
It is feeling the texture of a strawberry and knowing, without looking, exactly how much pressure will hold it and how much will turn it into jam.
In other words, Dexterity = Contact intelligence. The last inch problem in robotics.
You can hand a person an oddly shaped tool, and they’ll figure out how to grasp and use it. We don’t need prior training to hold a new object. We just do it.
Robots cannot do this. They are specialists, excellent at one task and brittle everywhere else. That gap is captured by Moravec’s Paradox, the observation that tasks humans find effortless, like picking up a coin or walking, are brutally hard for machines, even though they are superhuman at other things like mathematics.
You see, logic is computationally cheap. Running a chess algorithm requires very little energy. But the sensorimotor computation required to tie a shoelace is much more expensive.
The hard problems are easy, and the easy problems are hard
Evolution spent hundreds of millions of years optimizing the motor control of our body before it added the thin layer of cortex we celebrate as intelligence. The neocortex is young. Hands are ancient. Reverse-engineering the hand into a metal claw is fiendishly hard.
The mistake is thinking this is one problem. Dexterity is actually a stack of problems, and most of them live below the level of thought.
Man, why is it so hard to build a “hand”?
Robotic dexterity is where several hard problems converge. The first one starts with anatomy…