Great piece. Absolutely, regulation on airplane manufacturing would be an important consideration/potential roadblock to implementing this AM program at a large scale in Boeing and other airplane manufacturers. Specifically, although AM provides methods of producing lighter weight and cheaper parts, it begs the question of what has to be given up in quality (if any)? Testing the durability of AM produced parts against traditionally made ones, and showing equal or even greater performance will be key to getting buy-in/confidence from regulators..and even passengers like me!
Interesting piece! I would be curious to explore the tensions between social platform providers and actual advertisers in tackling ad frauds. For example, to a social network such as Instagram, is the incentive to reduce or increase the number of people your ads target? Most likely the latter, in which case, they “might” be more open to being lax on fake accounts, etc. P&G on the other hand wants to reach the most “real” accounts with the least amount of marketing dollars, but has very limited power in filtering for these accounts. Unless social media networks genuinely commit to drastically reducing fake accounts, ad fraud is here to stay.
General Mills should absolutely retain their R&D team, specifically for the reasons you stated around cultural differences between a nimble startup and a behemoth such as GM. Going the acquisition route can be viewed as a way of “hacking” the innovation system; however, I would recommend that GM works harder to create an environment where this kind of innovation is fostered and promoted internally.
I am very much in support of leveraging more data in making better decisions, whether in the healthcare sector, clothing etc. However, aside from the ethical ramifications, I also wonder about how nuanced factors such as diet, geographical location, socio-economic status, etc are factored into data analyzed from genetic formations. Specifically, what if a certain disease in a person is caused by the individual’s decision to pursue a certain lifestyle, versus having a particular genetic composition? In that scenario, viewing simply the genome sequence in isolation might lead to inaccurate conclusions. This might be something that has been already addressed by the scientists behind this research, but if not…I would be very worried.
Congrats to the team at BOH for addressing a market gap in the fashion space! You are right in your concerns about the potential ubiquity of applying Machine Learning to customer-oriented business. Data will remain king for centuries to come, and many more businesses and industries will utilize this data in making decisions and reducing costs. Thus leading to the bigger concern of the validity of this data. In BOH’s industry, you are right in considering the vast amount of data required to deduce any reasonable patterns in behavior; however, more and more businesses are taking the easier route and buying this data from third parties. This data, although easier to access, might be laced with all kinds of white noise and impurities. In this scenario, BOH will have to weigh the costs/benefits of gathering its own data versus accessing an existing pool.
A potentially revolutionary idea if, as others have mentioned, Made in Space Inc. can work to ensure high quality, and eventually attain a point where the need for human interaction is greatly reduced. Taking this to my ideal extreme scenario: imagine that space vessels no longer had to carry all the extra weight in spare parts on their ascent, and could source all their raw materials in space. The cost of space travel would potentially drastically reduce and more people/organizations would have access. Sounds like the next logical frontier is space mineral exploration!