Jay Smith
United Kingdom
๐—ฅ๐—ผ๐—ฏ๐—ผ๐˜ ๐—ช๐—ฎ๐—ฟ๐˜€: ๐—”๐—ฟ๐—ฒ ๐—›๐˜‚๐—บ๐—ฎ๐—ป๐—ผ๐—ถ๐—ฑ ๐—ฅ๐—ผ๐—ฏ๐—ผ๐˜๐˜€ ๐—ฅ๐—ฒ๐—ฎ๐—น๐—น๐˜† ๐—จ๐˜€๐—ฒ๐—ณ๐˜‚๐—น? $ABBN.ZU (ABB LTD) $NVDA (NVIDIA Corporation) $TSLA (Tesla Motors, Inc.) $SIE.DE (Siemens Aktiengesellschaft) $1810.HK (Xiaomi Corp) //๐˜—๐˜ข๐˜ณ๐˜ต ๐Ÿฃ ๐˜ฐ๐˜ง ๐Ÿค - ๐˜š๐˜ฆ๐˜ฆ ๐˜ค๐˜ฐ๐˜ฎ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต๐˜ด ๐˜ง๐˜ฐ๐˜ณ ๐˜ฑ๐˜ข๐˜ณ๐˜ต ๐Ÿค Robots are cool - think $TSLA Optimus dancing and Boston Dynamicsโ€™ Spot on a factory tour. But beyond the fun demos, are the humanoid robots promising to revolutionize our workplaces and homes by emptying the trash and stacking supermarket shelves really the solution? Humanoid Robots are like a Swiss Army Knife, impressive engineering, but whoโ€™s the buyer? ๐™„๐™ฃ๐™™๐™ช๐™จ๐™ฉ๐™ง๐™ž๐™–๐™ก ๐™ƒ๐™ฎ๐™ฅ๐™š ๐™ซ๐™จ ๐™๐™š๐™–๐™ก๐™ž๐™ฉ๐™ฎ Humanoids are marketed as the perfect alternative to humans in warehouses and factories globally. No breaks or time off, lower cost, higher uptime and multi-taskers once trained. ๐ป๐‘’๐‘Ÿ๐‘’โ€™๐‘  ๐‘กโ„Ž๐‘’ ๐‘Ÿ๐‘’๐‘Ž๐‘™๐‘–๐‘ก๐‘ฆ ๐‘โ„Ž๐‘’๐‘๐‘˜: Most major industrial facilities are now well standardized and structured for efficiency, they have repeatable workflows that are more suited to specialized robots than humanoids. Why would companies invest in robots that have so many additional parts for fingers and thumbs, legs, knees and feet, when they could just use gripping jaws and wheels? Then thereโ€™s the capital expenditure and expertise required to shift from human driven operations, to humanoids with teams of engineers to keep it all running. Most tasks that can be automated already have been, and the ones that havenโ€™t rely upon human judgement and adaptability. ๐™ƒ๐™ช๐™ข๐™–๐™ฃ๐™ค๐™ž๐™™๐™จ ๐™ซ๐™จ ๐™ƒ๐™ช๐™ข๐™–๐™ฃ๐™จ: ๐˜พ๐™–๐™ฃ ๐™๐™๐™š๐™ฎ ๐™๐™š๐™–๐™ก๐™ก๐™ฎ ๐™๐™š๐™ฅ๐™ก๐™–๐™˜๐™š ๐™๐™จ? Letโ€™s explore how well humanoid robots stack up against what they are trying to imitate. ๐ท๐‘œ๐‘ค๐‘›๐‘ก๐‘–๐‘š๐‘’ & ๐ต๐‘Ÿ๐‘’๐‘Ž๐‘˜๐‘ : Although robots donโ€™t need sick days, they do still have downtime. They require time for software updates, hardware inspection, cleaning, maintenance & calibration, repairs, and charging. Humans typically work 8 hours per day, 5 days a week. Including sick leave, public holidays and paid time off, itโ€™s around 250 days per year. Humanoids, once set up, can work up to 22 hours per day 6 days a week, with 2 hours daily for charging and inspections and a full day for software updates, cleaning, repairs, etc. Humanoids win on uptime. ๐ถ๐‘œ๐‘ ๐‘ก: Humans in emerging markets like Vietnam, China, Indonesia, etc typically get paid around $3/hr. They donโ€™t consume any electricity, there are no capital costs to be amortized, they donโ€™t require spare parts and the support infrastructure (HR, break rooms, Management Staff, Health & Safety, Administration work, etc) comes to around a 12.5% overhead or $0.40/hr. Salary: $3.00/hr Support/Infrastructure: $0.40/hr Total: $3.40/hr Humanoids donโ€™t get a salary, consume around $0.21/hr of electricity, need approximately $0.14/hr for spare parts, and require support infrastructure (Maintenance Bays, Software & Hardware Technicians, Management Platform, AI & Compute, Analysts & Administrators, etc) at $0.26/hr. The Humanoids could cost as little as $30,000 in 2030, meaning an Amortization cost of $0.63/hr. Energy: $0.21/hr Spare Parts: $0.14/hr Support/Infrastructure: $0.26/hr Capex: $0.63/hr Total: $1.24/hr If the assumption that Humanoids are just $30,000 each is correct, humanoids comfortably win on cost. However, if for example the cost only falls to $60,000 by 2030 the total cost would be $1.87/hour, which isnโ€™t quite as compelling. This also doesnโ€™t account for the cost of capital. The funds used to purchase the robots would likely utilize some sort of loan, so the true cost for humanoids will be higher in most cases. ๐ธ๐‘“๐‘“๐‘–๐‘๐‘–๐‘’๐‘›๐‘๐‘ฆ & ๐ธ๐‘“๐‘“๐‘’๐‘๐‘ก๐‘–๐‘ฃ๐‘’๐‘›๐‘’๐‘ ๐‘ : While the above metrics are easy to measure, this one is much more difficult and varies dramatically based on task and working environment. It can easily be argued that until AI improves substantially, humans are much better at handling edge cases. Irregularly shaped objects, clutter, spillages, etc. Alongside this, new tasks could take days or even weeks to train humanoid robots to carry out effectively, requiring simulations and testing. Some more intricate tasks are better suited to humans, we can fit in small spaces and have better dexterity and coordination than humanoids do currently. Finally, thereโ€™s accidents and safety. Humans are better at spotting and avoiding hazards, and can call emergency stops when appropriate. Humanoids, either require heavy monitoring for this, or could suffer from false positives, slowing down production, or not recognizing risks, resulting in collisions or costly errors. Based on the current technology, and where I expect it will be in 2030, Humans win this category. ๐‘†๐‘ข๐‘š๐‘š๐‘Ž๐‘Ÿ๐‘ฆ: It appears inevitable that eventually, Humanoids will surpass Humans in all but edge cases. However, self-driving cars serve as a perfect example of a technology that has actually taken much longer to mature than most investors and leaders anticipated. //๐˜Œ๐˜ฏ๐˜ฅ ๐˜ฐ๐˜ง ๐˜ฑ๐˜ข๐˜ณ๐˜ต ๐Ÿฃ ๐˜ฐ๐˜ง ๐Ÿค - ๐˜š๐˜ฆ๐˜ฆ ๐˜ค๐˜ฐ๐˜ฎ๐˜ฎ๐˜ฆ๐˜ฏ๐˜ต๐˜ด ๐˜ง๐˜ฐ๐˜ณ ๐˜ฑ๐˜ข๐˜ณ๐˜ต ๐Ÿค
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