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This was particularly interesting article and it has certainly piqued my interest. I would be curious to see if / how the Marines are able to get the IP from defense companies. If they do, how will defense companies be compensated and how will that be tracked? Will it save money or be even more costly? In addition, this can be concerning as a lot of these parts could be highly classified and the IP must be closely safeguarded. With added convenience, there is the trade-off of safety. Will it be harder to safeguard these closely held secrets if the specs are much closer to the front line? If lost, is the government to blame? How will defense companies react? I think this overall initiative makes total sense, but there are a lot of unanswered questions. I am curious to see where this ultimately ends up.

This was particularly eye-opening and was very interesting to read. It got me thinking about the public education system as a whole. Teachers are the ones that interact with students on a day-to-day basis and they recognize how difficult it is to apply a general curriculum to different classes. Does the system need to empower teachers more and take some decision-making ability away from administration? Does it make sense to give teachers a subsidy to dictate their own lesson plans? With the new focus on the different types of learning styles in students, TPT sounds like it will shine in the new educational environment. However, where do we need to go to start this change? Policy? Administration? Teachers? Or maybe even parents? And if TPT does begin to scale, how difficult will it be to make sure that the whole system is stable and sustainable as more money pours into the system? Education and money don’t always like each other.

On November 15, 2018, acm commented on Adidas and Additive Manufacturing :

I am definitely excited to see that shoe production is moving in this direction. It adds another level of choice for the consumer. However, do you think additive manufacturing / customization will replace all traditional forms of shoe production? Will there always exist a market for cheaper, generic sized shoes? If so, where is that balance and how should Adidas approach investment in both of these areas in the short-term vs medium-term? In another extreme case, if Carbon’s technology becomes easily accessible to the consumer, could consumers just skip Adidas altogether and create their own shoes? How does Adidas strike that balance in terms of innovation and cost for Carbon’s methodology?

As many people have pointed above, I think the idea of open innovation is great, but Lilly must be very careful with how they interact with the collaborators. In addition to the question of compensation, how should Lilly interact with collaborators when the process approaches more “sensitive” points such as the need for trials? Does Lilly conduct the trials itself? If Lilly is at any point being perceived as taking unfair advantage of collaborators, it could lead to a mass exodus of collaborators from the platform and make it virtually impossible to recoup the initial set-up costs for the platform. I love the idea of open innovation, but I wonder how difficult it is to properly incentivize people on all sides to actively participate in a for-profit setting.

Very fascinating article. One interesting thought that occurred to me while I was reading this was who should get the blame when the AI makes a “mistake” and the human acts based on that mistake? It might be easy to say that the human should, because they’re the one that made the ultimate decision, but if there is a gradual transition from human control to AI control, at what point would the blame shift? Is it always going to be “who” presses the final button? And if it is the AIs “fault”, are the developers the ones to blame? Or simply the AI itself? It seems like a hard question to answer, but a seemingly important one when the stakes seem so high.

I found this article particularly fascinating. As you mentioned in your article, a lot of of the congestion in LA is due to the lack of capacity or resident driving behavior on the highway system. If the majority of the problems ultimately stem from this, would it make more sense to concentrate resources on applying machine learning to the highway system? Is there a way to identify where the true bottleneck is? If so, are there effective ways machine learning can be applied to the highway system? In addition, with the Olympics coming to LA in 2028, LA seems to be in a time crunch to fix the overall traffic system. With this in mind, does it make sense to dedicate more resources to this initiative or other initiatives such as expanding the public transportation or highway system?