In response to your second question – this is not an area in which I think P&G should be spending resources to have in-house capability. This is on the low end of the technology spectrum of 3D printing in terms of tolerances, strength requirements, and complexity of setup, so I would be very inclined to outsource this effort. The only counterpoint is if P&G sees other areas of their business that might be require expertise in 3D printing, then it might be worth them developing that expertise themselves, but my hunch is that this is not the case.
I think the just-in-time delivery idea is a very cool concept, but raises some big safety/reliability concerns for me. Stryker needs to balance its ability to produce JIT with its ability to inspect JIT – it sounds great to print an implant on the spot and put it right into someone’s body, but some thought must be given to inspection. Screening for defects usually involves non-destructive testing that is performed by specially trained personnel and is not as well suited to decentralized production as 3D printing is. If Stryker is truly dedicated to JIT manufacturing of custom implants on-site while the patient is in surgery, they must also develop decentralized methods for inspection that can be readily automated and also performed JIT.
I like the LittleBits concept a lot, and I am not particularly worried about replicating others designs. I’m sure there will be quite a few copycats, but with limited opportunity for monetization by individuals, I think the main motivation of those using the kits will be to create new and interesting things.
Very interesting take on the unintended consequences of technology. My concern is with our reciprocation of the enemy’s tactics – is this data reliable enough to launch US attacks when weighed against the risk of collateral damage? I would be concerned that such geo-tagging could be manipulated, leading us to attack the wrong places, possibly leading to civilian casualties and subsequently hurting the cause.
Definitely interesting implications for such a speed-intensive industry, but my rather-uninformed view (I’m not from finance) is that RBC will downsize it’s research staff to cut costs while still improving speed. I’d think they might try to do more value-add work, but I don’t understand the business model enough – how does a company actually monetize the fact that its reports are better?
Sesame Credit developed out of necessity because a traditional credit scoring mechanism didn’t exist in China, and I agree it has some interesting implications, but I’m not sure I agree that the data will be used to allocate resources to the most credit worthy and productive individuals. With machine learning, it is simply likely to see what success looks like and give you more of the same – I’d be worried it is reinforcing existing socioeconomic structures within China. I can envision this type of social credit scoring system devolving into a caste system that put some people into socioeconomic situations from which they cannot escape.