Humanoid robots: 1. Forecasts: Goldman says $38bn by 2035. Barclays says $40bn base, $200bn if things go right. BofA models 10 million units that year, up from 20,000 in 2025. Morgan Stanley waves at $60tn. Near term beneficiaries are factories: 72% of 2027 installs in logistics, manufacturing and automotive. My view: technology is moving faster than expected. I think we are only three years away from seeing millions of humanoid robots deployed. 2. The bottleneck is not the AI: The brain is the cheap, solved part. Memory will still be the constraint but the hard part is the body. This is a machine-tool problem, not software. A humanoid is a car in miniature, thousands of fine-tolerance parts, and the edge sits with whoever already has automotive and precision-mechanics DNA. Guess who have ALREADY the capacity to produce millions of EV cars? CHINA. 3. The map, by layer: • Brain (semis + models): $NVDA, and the memory it needs in $MU , SK Hynix, Samsung. Cheap, crowded, commoditizing. • Brawn (the actual bottleneck): screws and reducers in Hiwin, THK, Harmonic Drive, Nabtesco, Jiangsu Hengli. Motors in Nidec, Estun, Inovance. • Sensors and structure: force/torque, vision and connectors in Sensata, TE Connectivity, Sony, Keyence, $OUST. • Rare earths (the input under all of it): $MP, Lynas, JL Mag. China controls over 90% of magnetic rare earths. • Integrators (the full robot): Tesla, plus a heavily Chinese field, UBTech, Xiaomi, BYD, XPeng, and Hyundai via Boston Dynamics. Morgan Stanley data point that gets buried: 73% of confirmed humanoid participants are Asian, 56% Chinese. The US has $TSLA , $NVDA , and not much else on the hardware side. As always I prefer to play the picks-and-shovels under it, the screws, the rare earths, the grinding-machine bottleneck, get paid whether or not Optimus or Figure is the one that scales.