"Real technical challenges remain around speed, safety, and the general capability of these robots — as well as how to make their training more scalable and make the hardware more reliable. "
Great summary of it. Nicely written article thanks!
As a Management Engineering student, I agree that automation is going to be the biggest game-changer for factories and warehouses (with AGVs and tote retrieval systems) both scaling via AI.
However, the 'low-margin' issue you mentioned is critical. Here in Italy, for example, the economy is driven by SMEs (Small and Medium-sized Enterprises) that often struggle to find the break-even point between the high upfront cost of robots and the actual long-term benefits.
The Nike example really ilustrates how deformable materials are still a huge bottleneck for automation. What struck me most was the point about tax breaks vs upfront subsidies, that difference in how governments incentivize automation probably explains more than we think about the US-China gap. Are we seeing any movemnt toward more direct subsidies, or are companies just trying to work around the current system?
I dont think so, the US is reluctant to directly spend government money to achieve social goals for cultural reasons, so we are likely stuck with a mess of inefficient partial moves
Great article! As well as your great points, the thought process behind how you automate a previously manual task is super important, distilling them down to key elements and thinking from first principles the correct way to automate them.
"Real technical challenges remain around speed, safety, and the general capability of these robots — as well as how to make their training more scalable and make the hardware more reliable. "
Great summary of it. Nicely written article thanks!
Thank you!
🔥🔥🔥
Nicely written! (As an engineer formerly employed in manufacturing automation)
Glad it holds up then!
As a Management Engineering student, I agree that automation is going to be the biggest game-changer for factories and warehouses (with AGVs and tote retrieval systems) both scaling via AI.
However, the 'low-margin' issue you mentioned is critical. Here in Italy, for example, the economy is driven by SMEs (Small and Medium-sized Enterprises) that often struggle to find the break-even point between the high upfront cost of robots and the actual long-term benefits.
Loved the reading, thank you.
It's a huge game changer.
Thanks, I am quite optimistic that long term cheap robots will solve this problem
The Nike example really ilustrates how deformable materials are still a huge bottleneck for automation. What struck me most was the point about tax breaks vs upfront subsidies, that difference in how governments incentivize automation probably explains more than we think about the US-China gap. Are we seeing any movemnt toward more direct subsidies, or are companies just trying to work around the current system?
I dont think so, the US is reluctant to directly spend government money to achieve social goals for cultural reasons, so we are likely stuck with a mess of inefficient partial moves
Yeah, this is an interesting part of it. I see a lot of reluctance in some sectors...
Great article! As well as your great points, the thought process behind how you automate a previously manual task is super important, distilling them down to key elements and thinking from first principles the correct way to automate them.
Thank you!
Love this!
Thanks!
would love your thoughts on some of my stuff. follow me back, I could DM you?
Honestly a great read! Thanks for putting together this article Chris :)
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