Kendrae's Profile

Your question around consolidating operations vs maintaining multiple additive manufacturing operations is an interesting one! While it may reduce costs to consolidate operations, I would recommend Adidas maintain multiple operations and focus on the customizable aspect of 3D printing. I think Adidas can create demand by allowing customers to design their own shoes (with limitations, based on a few standard customizable features to enhance performance, fit, look) in a unique way using 3D printing. Since Adidas is allowing customers to customize their own shoes, they will be able to function by producing only after the shoe has been ordered and, with multiple locations, will be able to quickly deliver the shoes to the customer. In this way, they will be able to provide a premium product that a customer will be willing to pay more for and they can raise prices. Additionally, as seen in our recent Nike case, athlete endorsements are highly valuable in this industry and Adidas will be able to maintain a high price tag if they are able to sponsor/gain the endorsement of a high-profile athlete who supports the merits of a 3D printed shoe.

This is a very interesting application for additive manufacturing, especially given the level of customization that it provides. While Align may be losing market share to direct to consumer companies like SmileDirectClub, Align has the advantage of being closely tied with orthodontists and dentists. SmileDirectClub has invested heavily in marketing directly to consumers, including millenials, with little to no support provided by medical providers. In fact, the American Dental Association actually released a resolution strongly discouraging people from using “DIY orthodontics” like SmileDirectClub, due to the potential for harm when aligners are used incorrectly without orthodontic supervision (e.g., bite problems, enamel wear, even tooth loss) [1]. Align has the market advantage here since medical providers such as orthodontists and dentists are highly trusted and will be able to advise patients against using these direct to consumer brands since they have the potential to be dangerous. From this perspective, I think Align may be able to minimize their investment in advancing their materials and manufacturing processes if they can use their trusted position with medical providers to recommend their product over others. In this way, Align may be able to save by investing more in marketing and medical provider visibility rather than advancing their technology.

[1] Electronic Health Records, http://www.ada.org/en/publications/ada-news/2017-archive/november/ada-discourages-diy-orthodontics-through-resolution.

This is a particularly interesting topic in the context of health insurance and long-term care insurance. As people gain more information about their genetic sequencing from tests like 23andMe, they will be more informed about the risks they are facing in the future. This will better inform their decisions about what type of health and long-term care insurance to purchase, since they are more aware of their risk profile. While this will be beneficial to consumers, it also runs the risk of increasing premiums for insurance since, presumably, riskier consumers will be more frequently requesting insurance, while less risky consumers will be less likely to purchase insurance.

Additionally, as consumers are more informed, there will be information available that may influence an insurance company’s decision to allow someone to purchase insurance. For example, a woman purchasing long-term care insurance knew she had inherited a gene which increased her likelihood of developing Alzheimer’s in the future, but she did not disclose that information to her insurance provider, which made her take multiple memory tests prior to allowing her to purchase insurance [1]. In the future, insurance companies may require individuals to use genetic testing like 23andMe to determine their risk profile in order to evaluate what their insurance premium should be. Hopefully, this does not happen, since pre-existing conditions should not influence an insurer’s decision to insure someone and/or how much to charge them.

[1] Kolata, Gina. “New Gene Tests Pose a Threat to Insurers.” The New York Times, The New York Times, 12 May 2017, http://www.nytimes.com/2017/05/12/health/new-gene-tests-pose-a-threat-to-insurers.html.

I think your recommendation to use images made available by the public for Google Maps is a great one! This would allow for maps to function based on open innovation, which would allow for updates to be made to Google Maps when a Google Street View car is unable to pass through that area to gather updated images. I have noticed recently that Google is requesting additional information from me as I use Google Maps to improve the accuracy of their traffic estimates (e.g., asking questions such as: “How busy was the bus you rode to school this morning?”). This shows that Google is attempting to use crowd-sourced information to improve their estimates of traffic, which they could also apply to their mapping accuracy (by asking questions about specific locations to people who are frequently in that area).

Your second question is very interesting and leads me to believe that the market should be entirely efficient if all hedge funds are using machine learning algorithms to trade. In this case, hedge funds will need to use their machine learning technology and algorithms as their competitive advantage over other funds in order to extract any sort of value. This is an interesting concept to think about because trading will ultimately become very similar to the tech industry since firms with the best technology will have an advantage in the market. In this case, the skillsets of the traders will need to be entirely different than they are today and traders with strong technical and coding skills will be highly sought after. I am curious to see how other hedge funds begin to use machine learning and who they will hire in order to strengthen their technology platforms.

Your question regarding what the role of human composers looks like in the future is an interesting one. Already, there are artists that are creating music entirely based on AI. For example, YouTube star Taryn Southern recently released an album using an open source AI platform called Amper, which allowed her to select several parameters such as “genre, instrumentation, key and beats per minute” to create her songs [1]. She mentions that she does not have a traditional music background and Amper was a low-cost option that allowed her to enter the music industry without recruiting a band. While it is admirable that AI allowed someone to enter the music industry who may not have otherwise been able to do so, it calls into question how much a human composer must be required to input in order to call a song his or her own. In this case, Southern generated backing music for her vocals using AI. If she instead released the album with only backing music (without vocals), could the music be considered her own? How much of a “composer” is Southern since she did not truly compose her own backing music? These are interesting questions that will likely become more prevalent as more artists begin to use AI in their music.

[1] Love, Tirhakah. “Do Androids Dream of Electric Beats? How AI Is Changing Music for Good.” The Guardian, Guardian News and Media, 22 Oct. 2018, http://www.theguardian.com/music/2018/oct/22/ai-artificial-intelligence-composing.