Figure 03, our 3rd generation humanoid robot

"Building Figure won’t be an easy win; it will require decades of commitment and ingenuity."

"Our focus is on what we can achieve 5, 10, 20+ years from now, not the near-term wins."

At least it's not Musk's forever "next year".

The problem with the principled approach to high-uncertainty projects is that if you slowly execute on a sequential multi-year plan, you will almost certainly find out in year 9 that multiple of the late-stage tasks are much harder than you thought.

You just don't know ahead of the time. Just look at how many corporations and research labs had decades-long strategies to build human-like AI that went nowhere. And then some guys came up with a novel architecture and all of sudden, you can ask your computer to write an essay about penguins.

Musk's approach is that if you have an infinite supply of fresh grads who really believe in you and are willing to work crazy hours, giving them a "next year" deadline is more likely to give you what you want than telling them "here's your slow-paced project you're gonna be working on for the next decade". And I guess he thinks to himself that some of them are going to burn out, but it's a sacrifice he's willing to make.

We are nowhere near the same for autonomous robots, and it's not even funny. To continue to use the internet as an analogy for LLMs, we are pre-DARPANET, pre-ASCII, pre-transistor. We don't even have the sensors that would make safe household humanoid robots possible. Any theater from robot companies about trying to train a neural net based on motion capture is laughably foolish. At the current rate of progress, we are more than decades away.

Neural networks for motion control is very clearly resulting in some incredible capability in a relatively short amount of time vs. the more traditional control hierarchies used in something like Boston Dynamics. Look at Unitree's G1

https://www.youtube.com/shorts/mP3Exb1YC8o

https://www.youtube.com/watch?v=bPSLMX_V38E

It's like an agile idiot, very physically capable but no purpose.

The next domain is going to be incorporating goals and intent and short/long term chains of causality into the model, and for that it seems we're presently missing quite a bit usable training data. That will clearly evolve over time, as will the fidelity of simulations that can be used to train the model and the learned experience of deployed robots.

This feels incredibly generous. I'm pretty sure his approach is that he needs to keep the hype cycle going for as long as possible. I also believe it's partially his willingness to believe his own bullshit.

I’m sure they could pretty easily spin up a site with 200 of these processing packages of most sizes (they have a limited number of standardized package sizes) nonstop. Remove ones that it gets right 99.99% of the time and keep training on the more difficult ones, the move to individual items.

Caveat: I have no idea what I’m talking about.

If you can make it look believable on camera for 15 seconds under controlled studio conditions... it's probable you can do it autonomously in 10-15 years. I don't think anyone is going to be casually buying these for their house by this time next year, but it certainly demonstrates what is realistically possible.

If they can provably make these things safe, it will have huge implications for in home care in advanced age, where instead of living in an assisted living home at $huge expense for 20+ years, you might be able to live on your own for most of that time.

I am cautiously optimistic.

It was never about the sensors. It was always about AI.

This only highlights the fact that making a cool prototype do a few cool things on video is far, far easier than making a commercial product that can consistently do these things reliably. It often takes decades to move from the former to the latter. And Figure hasn't even shown us particularly impressive things from its prototypes yet.

An arm moving against gravity has a higher draw, the arc itself creates characteristics, a motion or force against the arm or fingers generates a change in draw -- a superintellligence would need only an ammeter to master proprioception, because human researchers can do this in a lab and they're nowhere near the bar of 'hypergenius superintelligence'.

I'm not surprised that a Honda Civic can't navigate the Dakar Rally route..

They didn't go nowhere; they just didn't result in human-like AI. They gave us lots of breakthroughs, useful basic knowledge, and knowledge infrastructure that could be built off for related and unrelated projects. Plenty of shoot for the moon corporations didn't result in human-like AI either, but also probably did go nowhere, since they were focused on an all or nothing strategy. The ones that do succeed in a moonshot relied on those breakthroughs from decades-long research.

I'm not going to get into what Musk has been doing because I'm just not,