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Disagree. This argument is a huge straw man. We are still a long way off from 100% lights-out factories being the norm for most industries. Even in IT manufa

Disagree. This argument is a huge straw man. We are still a long way off from 100% lights-out factories being the norm for most industries. Even in IT manufacturing which is highly-automated, Foxconn employs hundreds of thousands of people in China. Most automotive factories employ several thousand workers.

jtraffic 9y ago
That's fair. But I guess I think of it as a somewhat continuous transition from human to machine manufacturing. Yes, currently manufacturing uses lots of humans, but that is changing, and the pace of change has not, AFAIK, reached any plateau. What I think matters, is where we are going, not where we are. You give China as evidence of the human dominated state of manufacturing. I give it as evidence of the shift toward robot dominated manufacturing: https://www.technologyreview.com/s/601215/china-is-building-a-robot-army-of-model-workers/ https://www.technologyreview.com/s/601215/china-is-building-...
mncharity 9y ago
Many years ago there was a startup which did web-storefront on-demand laser-cut custom-fit khakis. They did the largely-manual stitching in the US, rather than deal with the cost and delay of shipping further. My fuzzy recollection is they sold out to Levi's, which mismanaged it into nonexistence. The patents prevented replacement. And the stitching factory used eventually died. So at least some partially-automated traditionally-low-margin industry is/was possible in the US. But the usual issues of losing needed industry infrastructure still apply.
Houshalter 9y ago
Machine learning has improved by leaps and bounds in the last half decade. Much of that progress has yet to make it out of the lab. But that's typical for new technologies, and will happen eventually. It's not a huge technological leap from "robot learns to play Dota" to "robot learns to stitch baseball gloves". Machine vision and reinforcement learning were always the technologies holding back interesting applications of robotics. And now they are basically solved problems.

jtraffic 9y ago

That's fair. But I guess I think of it as a somewhat continuous transition from human to machine manufacturing. Yes, currently manufacturing uses lots of humans, but that is changing, and the pace of change has not, AFAIK, reached any plateau. What I think matters, is where we are going, not where we are. You give China as evidence of the human dominated state of manufacturing. I give it as evidence of the shift toward robot dominated manufacturing: https://www.technologyreview.com/s/601215/china-is-building-a-robot-army-of-model-workers/ https://www.technologyreview.com/s/601215/china-is-building-...

mncharity 9y ago

Many years ago there was a startup which did web-storefront on-demand laser-cut custom-fit khakis. They did the largely-manual stitching in the US, rather than deal with the cost and delay of shipping further. My fuzzy recollection is they sold out to Levi's, which mismanaged it into nonexistence. The patents prevented replacement. And the stitching factory used eventually died. So at least some partially-automated traditionally-low-margin industry is/was possible in the US. But the usual issues of losing needed industry infrastructure still apply.

Houshalter 9y ago

Machine learning has improved by leaps and bounds in the last half decade. Much of that progress has yet to make it out of the lab. But that's typical for new technologies, and will happen eventually. It's not a huge technological leap from "robot learns to play Dota" to "robot learns to stitch baseball gloves". Machine vision and reinforcement learning were always the technologies holding back interesting applications of robotics. And now they are basically solved problems.