Jeffrey J Jefferson
For Nike, I believe the long-term benefits of 3D printing will remain for proto-typing, versus mass production. Nike already has a scaled, low cost manufacturing footprint and it would take many years for 3D printing to bring its unit cost down to compete with Nike’s existing footprint and justify the massive capital investment required to 3D print at scale. Additionally, the benefits of 3D printing for manufacturing purposes: detail, flexibility, customization, texture and substrate combinations, are less important for running shoes.
I imagine many start-ups looking for funding share the concerns of the effects Epic Provisions experienced when GM invested in their business. GM is, in many ways, the epitome of the type of company they are trying to disrupt and the cultural clashes likely will be stark. 301 inc should push to remain as “incubator-like” for as long as possible in order to delay these inevitable cultural conflicts. From the start-up entrepreneurs’ point of view, they must balance the potential cultural disruption (versus taking more traditional VC money) with the likelihood of a premium strategic exit by selling to GM one day.
I agree crowd-sourcing ideas from avid fans for new products is a great way to keep LEGO’s most passionate fans engaged, while accelerating the new product development process. Additionally, open innovation aligns directly with the underlying idea of LEGOs (at least for me personally): fostering an open, creative, exploratory mindset by constructing plastic blocks in seemingly endless combinations.
I do worry a bit that this concept is opening LEGO up for further competition in the toy space. By inspiring fans to become creators, you are fostering the development of the next “big thing,” however it is more likely than not that an inspired fan would try to develop this concept for personal gain, versus sharing with LEGO for free.
I echo the sentiment in Michael Scott’s post above – it concerns me that Netflix is able to use this data to manipulate viewing behaviors – specifically binge watching (which I believe they encourage and strive for). Just as social media companies, mobile application developers, and smart phone manufacturers are trying to make their products as addictive as possible, Netflix is using our viewing behavior data to do the same. This strive for addiction (perhaps a harsh word, but fair in this case) will have long-term negative consequences for Americans and people across the world, and machine learning is making this quest ever easier.
I also worry about Netflix’s ability to understand our viewing behaviors will assist them in influencing our opinions, as we have seen nefarious users of social media accounts do recently.
I think the fourth paragraph underestimates how this Cambridge Analytica scandal, as well as other recent data exposure scandals and data breeches (Equifax, Target, etc.), will impact how people think about sharing personal information and other data with companies. It will not happen overnight, but longer-term people are going to be more careful with what they share as they become aware of how their data is used (thanks to articles like this) and how easily it can be hacked by nefarious actors. Less accessible data could potentially mute the benefits of machine learning for consumer data analysis.
This seems like a fantastic idea in theory, but I still wonder about the actual execution of astronauts or other space-operating individuals working the machines. Is it possible for the machines to be operated remotely from trained professionals in Houston or other NASA stations? If not, I wonder what is the training time required to learn how to operate these machines, especially in the challenging conditions that working in space presents.
The transition to government to commercial-funded model also works nicely in theory, but it can only happen as quickly as overall space spending moves out of government – which I know is happening, but at what pace?