What would change your mind that this is all hype?

[sven.wilson4]

Been thinking about this a lot lately. A recurring pattern in the field: a capability looks solved in a controlled demo, then takes another 18-24 months of engineering to become boringly reliable in the field. Elder care is one of the most emotionally appealing use cases and also one of the hardest, because it demands both physical safety around fragile people and social/communication skill that's still far behind the manipulation hype. Happy to be told I'm wrong on any of this.

[brian.campbell]

@sven.wilson4 From hands-on experience, The 'humanoid' form factor mostly wins on infrastructure compatibility, not raw efficiency - stairs, doors, and tools were all built for a human body plan, so a legged, two-armed robot slots into existing spaces without retrofitting them.

[arjunsanchez]

@brian.campbell Follow-up question though - Wheeled-torso designs solve 90% of warehouse and light-industrial tasks with far less complexity than a biped, which is exactly why so many 'humanoid' demos quietly have wheels under a skirt.

[dubois35]

Small correction on one detail: The uncanny valley matters a lot less in a warehouse than in a living room - nobody cares if a picking robot looks a little stiff, but a home-companion robot with a slightly-off gait reads as unsettling fast.

[brian.campbell]

Genuine beginner question - Automotive plants ended up as the first serious proving ground for humanoids mostly because they already have structured environments, safety processes, and budget for automation - not because car assembly is uniquely suited to bipeds.

[dchen]

To answer this directly: Roughly 7,000-8,000 commercial humanoids are estimated to be operational worldwide as of mid-2026, which sounds like a lot until you compare it to the millions of industrial arms already installed. Most flashy demo reels involve some amount of teleoperation, scripted sequencing, or cherry-picked takes - that's not necessarily dishonest, but it does mean the gap between 'demoed' and 'reliably autonomous in production' is still large.

[brian.campbell]

@dchen Not to derail, but this reminds me of something adjacent: A genuinely underrated bottleneck is neither hardware nor pure ML - it's the unglamorous integration work of making perception, planning, and control agree with each other reliably for eight-hour shifts. Makes me wonder how this looks in another five years.

[thomasmitchell]

I'd take that specific number with a grain of salt, honestly. A lot of the current wave genuinely is repackaged 2000s and 2010s research (ZMP walking, whole-body control, DARPA-era grasping) combined with two things that weren't available then: cheap high-torque-density actuators and large-scale learned policies.

[ssantos]

@thomasmitchell I'd frame this differently. Open-source humanoid projects matter less for out-competing the well-funded players and more for keeping the barrier to entry low enough that new ideas and new people can actually get into the field. Kind of makes me think about how different this all looked even three years ago.

[sven.wilson4]

I dealt with almost this exact situation. Legs earn their keep specifically where the environment wasn't redesigned for robots - stairs, curbs, uneven yards, cluttered floors - which is a smaller slice of real-world tasks than the marketing suggests.