Figure 03, our 3rd generation humanoid robot

All of the examples in videos are cherry picked. Go ask anyone working on humanoid robots today, almost everything you see here, if repeated 10 times, will enter failure mode because the happy path is so narrow. There should really be benchmarks where you invite robots from different companies, ask them beforehand about their capabilities, and then create an environment that is within those capabilities but was not used in the training data, and you will see the real failure rate. These things are not ready for anything besides tech demos currently. Most of the training is done in simulations that approximate physics, and the rest is done manually by humans using joysticks (almost everything they do with hands). Failure rates are staggering.

The last example they show (pick up package from pile, put it label-down on conveyor, repeat) seems to be the most realistic. They even have an uncut video of their previous model doing that for an hour on twitter [1].

I'm not sure that task needs a humanoid robot, but the ability to grab and manipulate all those packages and recover from failures is pretty good

1: https://x.com/adcock_brett/status/1931391783306678515

> I'm not sure that task needs a humanoid robot

An industrial robot arm with air powered suction cups would do the trick... https://bostondynamics.com/products/stretch/ ...

... So the task they work best at is the task there is already cheaper better robots specialized for.

I feel like we're entering the era of general and inefficient solutions to problems.

Like LLMs being used to pick values out of JSON objects when jq would do the job 1000x more efficiently.

This is what this whole field feels like right now. Let's spend lots of time and energy to create a humanoid robot to do the things humans already decided humans were inefficient at and solved with specialised tools.

Like people saying "oh it can wash my dishes for me". Well, I haven't washed dishes in years, there's a thing called a dishwasher which does one thing and does it well.

"Oh it can do the vacuuming". We have robot vacuums which already do that.

There were plenty of digital circuit engineers back in the 90s that said microprocessors were general and inefficient solutions to problems.

And if you needed it programmable, well an FPGA was still almost as general and far more efficient than a microprocessor.

Guess what won.

As a hardware engineer I hear this a lot from software/electrical folks.

It's Moore's law that largely drove what you describe.

Moore's law only applies to semiconductors.

Gears, motors and copper wire are not going to get 10x faster/cheaper every 18 months or whatever.

10 years from now gears will cost more, they will cost what they cost now plus inflation.

I've literally heard super smart YC founders say they just assume some sort of "Moore's law for hardware" will magicallyake their idea workable next year.

Computing power gets, and will continue to get, cheaper every day. Hardware, gears, nuts, bolts, doesnt.

It is not the gears, motors and copper wire that are bottlenecking robots. It is the software and computing. We can already build a robot hand that is faster, stronger, more dexterous, etc. than a human hand. What we can't do right now is make the software to perceive the world around it and utilize the hand to interact with it at human levels. That is something that needs computing power and effective software. Those are things that get, and will continue to get, cheaper every day.