It is so interesting to read that BigApps produced a parking space finder application. As a former New Yorker and frequent visitor of the city, I had no idea such an application existed. Parking can be one of the most frustrating experiences in New York, especially for families visiting the city from places like Queens, the Bronx, or other less economically unequal locations. This is the kind of problem that falls in the middle, since the poorest residents cannot afford a vehicle, and the wealthiest can afford convenient transportation. Of course, New York has an extensive public transportation network, which reduces the need for personally owned vehicles, generally. The larger point is that this program can benefit from wider publicity. By increasing the awareness of the kinds of city problems that can be ameliorated by BigApps, especially in poorer neighborhoods, the city has a tremendous opportunity to inspire students to pursue STEM disciplines.
Your point about the weaknesses of the incentives for innovative solutions is well said. It did not seem immediately clear what outside entities had to gain from expending resources to improve BOC. Additionally, a central bank must continually make efforts to maintain a reputation as a neutral player. Perhaps by rigorously sourcing the academic sector for solutions to BOC challenges, the bank can maintain a dispassionate stance towards industry while retaining an inflow of positive ideas for its own process improvements.
I believe addressing maintenance concerns will be most important as time progresses. One of the side benefits of owning a home is the ability to renovate it over time to keep up with the latest fashions and trends. As you mentioned, building codes are a crucial element of the construction and housing industries. The current requirements for renovation require compliance with these codes as they stand today and are only understood in the context of conventionally constructed buildings. I will be interested to see whether or not separate building codes will emerge for buildings constructed using nontraditional methods versus conventionally constructed buildings or whether new codes will blend the two different types of construction.
As you wrote, additive manufacturing has shown tremendous potential and the Indian government has sent a powerful message by setting a goal of using additive manufacturing on the moon. I would be curious to learn more about the mechanics of accomplishing such a task. How soon before additive manufacturing will pay for itself in this sector? Additionally, will India continue to rely on 3rd parties to transport its materials into space? Additionally, what benefits may be realized as the additive manufacturing technology improves to be able to use a greater variety of materials to build structures in harsh environments. Finally, in the high stakes realm of space transportation, will open innovation solutions be precise enough to be useful? I am excited to see how it turns out.
We have learned that the potency of machine learning algorithms is correlated with the quantity and quality of the data on which a machine is trained. You mentioned that this firm has access to one of the largest clinical data sets in the world. Wouldn’t a tremendous amount of resources be required to collect the data on which to train in order for any internal machine learning benefit to be realized? Is there any evidence to say that the benefits of administrative data collection would outweigh the cost of the time and labor investment required to accomplish such a task?
I understand the concern of influencers risking backlash from their followers as their content appears more aligned with corporations. I would be interested to learn how long these ad hoc partnerships between influencers and corporations persist. Given the fact that influencers face a perennial tradeoff of producing new content versus building and sustaining an audience I wonder how sustainable this model is in the long term. Additionally, internal to these corporations, what is the effect of friction between in-house marketing efforts and marketing efforts outsourced to machine-learning matched influencers? Can the organization keep up and learn from the influencers to save on their own marketing costs?