Mike, your point regarding the impact of labor arbitrage through offshore is very interesting, and I had not thought about the positive benefits for the US economy stemming from increased use of additive manufacturing. I certainly think embracing additive manufacturing is the best way to revitalize the US manufacturing industry. My concern, though, is how do we as a society ensure that workers from the manufacturing industry who have steadily lost their jobs over the past few decades are continually left behind? What is our society’s obligation to provide economic opportunity, training programs, or education that can build a new workforce equipped to add value in this new age of manufacturing?
There is a lot of well-founded skepticism around the value of mass customization to the consumer, especially regarding shoes. I agree with Christie, though, that there is huge potential for Adidas to be a first mover and change the purchase cycle Dan references. I think Adidas should be creative and explore other technologies that can further disrupt this purchase process. If it is possible, maybe Adidas costumers could send in either measurements or pictures of their feet to create a customer profiles that can then inform customized 3d-printer shoes in all categories. While obviously there are significant costs, the ability to produce shoes customized to a consumer would increase the lifetime value of any consumer by locking them into Adidas products.
It seems like the real issue is how to efficiently input accurate date into the algorithm so it can learn to produce correct outcomes. I optimistically hope that this will become easier as more and more of the healthcare system becomes digitized. I’d imagine raw data would need an intense quality control even when information is digital, but this could alleviate some of the pain. I also wonder if our expectations are too high. Can AI like Watson Health already add value by augmenting the work of doctors? Was IBM too ambitious with its goals and could it have had more of an impact attempting to complement doctors rather than attempt to take away much of their work?
Yes, I think the Marine Corps sees no limit on what additive manufacturing can produce although a ten year time horizon is probably not realistic. I think a more achievable goal is 3D printing ammunition. This would resolve a huge supply and logistics issue if small units can provide the right quantity and type of ammunition on the spot. As Marines, we constantly stress about having the right ammunition and enough of it going into a fight, and the capability of self-generating ammunition would be huge.
I do think other services are pursuing it but I don’t know of specific programs.
Joe, glad to see the Navy is making progress (albeit slow) towards this new CBM model. I completely agree with your concerns regarding bureaucratic inertia but wonder about the costs of this model. My guess is that costs are relatively high as this sensing technology and the associated algorithm probably require significant upfront investments. It probably makes sense, though, for the Navy because of the highly expensive nature of the Navy’s equipment. The Marine Corps could also greatly benefit from this CBM model but I highly doubt it will be cost effective enough any time soon for Marine Corps adoption. Many of the maintenance problems the Corps faces are due to wear and tear of relatively simple, low cost items. The Marine Corps is betting that it can scale additive manufacturing to the point that 3d printing low costs items on the spot is easier and more cost effective than having to ship them to dispersed units across the globe.
Jake, very interesting update on Fitbit, and I’m somewhat disappointed to learn that the Apple watch seems to have knocked off Fitbit as the top tech wearable. My instinct is consumers love the versatility of the Apple Watch and how it not only tracks useful data like Fitbit does but also integrates with their iPhone and other Apple products. In a world where share of the wrist is a real competition, I worry about Fitbit’s and other comparable products’ chances of survival. Focusing on more relevant data especially related to healthcare makes sense, but I am not sure if that is compelling enough to convince a consumer to opt out of an Apple Watch. I also wonder how does a newer product like Whoop compete with Apple and Fitbit? Do you see any machine learning aspects which Whoop can leverage to gain a competitive advantage?
Ian, love this choice of topic, and thanks for highlighting the great work Neighborly is doing. I really like the idea of giving members of a community more control over how their money is being spent. I worry, though, that Neighborly could unintentionally be making communities less democratic by giving a disproportionate amount of influence to those wealthy enough with assets and liquidity to purchase bonds and drive project spending. I think a possible counter is that Neighborly frees up the government to spend money in complementary rather than overlapping ways to Neighborly. I would like to see Neighborly potentially work with larger organization and companies who could finance projects that other members of the community can’t afford but certainly need.
Great post, Matt, and I think this is a highly interesting debate. Just a quick clarification, the term “agent” in this context typically refers to someone who enters into a contractual agreement with CIA to provide information, usually in a clandestine manner. CIA officers manage these agents while CIA analysts are the ones who make intelligence assessments which you discuss here. As a former human intelligence officer, I am very excited about the idea of crowdsourcing leads which solves a “top of the funnel” issue with counterterrorism efforts. However, I think effective agents, ie sources with direct access to the actual terrorists and their operations, will remain the critical aspect of successfully mitigating this threat. Crowdsourcing tips is certainly helpful and can provide useful context, especially utilizing new technology like Palantir to process this information, but it will not replace the value of validated information collected through clandestine operations.
Uber is a great example of how technology has led to this incredibly valuable service which has revolutionized transportation and has the potential to continue driving innovation, especially through the use of machine learning. Uber’s rise also shows the second and third order consequences, in this case the detrimental effect on drivers as Uber pushes to become more efficient. In some ways, Uber’s contribution to the gig economy has allowed many people to generate income in a way that is flexible to their schedules. But, it is also forcing drivers to perform more and more work to make any significant profit. I personally think Uber needs to do more to invest in their drivers and begin to treat them more as employees, especially the ones who clearly drive Uber as their full time jobs. Uber should set a model of corporate responsibility by mitigating the impact of machine learners on the “losers” of this megatrend.