AJB

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I stand corrected. My apologies, Kentucky Freud Chicken!

It is great to read that Stryker is not only using additive manufacturing to prototype its products more quickly but that it is also able to create superior products using AM (e.g. the implants that reduce risk of rejection and infection). I think the cost issue that you raise is an important one. How do we weigh the benefits of reduced infections, for example, with the additional cost of manufacturing implants using AM? I agree with prior comments that I think these costs will come down over time, making mass producing medical devices using AM more feasible. With regard to your second question, I think that physicians will likely need to continue to interact with the patients in order to ensure that that medical devices are appropriate for their condition but I think that medical device manufacturers will need to create close relationships with the physicians and/or industry groups in order to ensure that it is capturing the data it needs to improve its products.

I agree that GE has a great opportunity to be a leader in developing applications for AM beyond prototyping and I agree with your assessment that they should look to adopt AM across its business lines as a means of proof of concept. To your question of how can GE accomplish more widespread adoption across the firm, I think GE should focus on AM as a strategy for cost reduction. As both you and Brett mention, GE has been facing financial challenges and finding ways to lower costs through AM could be a good incentive for other business lines within GE to adopt AM. Beyond costs, I think that GE leadership can also attempt to get the business lines excited about the opportunity to be at the forefront. As you mention, GE can be on the slow slide of innovation. I can imagine that this is likely frustrating for some employees. By giving the business lines the autonomy and encouragement to pursue AM, GE employees could get excited about the prospect of being on the cutting edge and look for ways to incorporate AM into their business lines.

I believe the questions you (and Kentucky Fried Chicken) raised will be some of the biggest moral questions we have to answer in our lifetimes. I personally don’t believe in altering characteristics such as eye color and worry about the discrimination issues that you raise, as well as how we will go about determining which alterations are allowable versus which ones aren’t.

I think you raise a really important point about ensuring that the crowdsourced data represents a diverse population. This is a great example of how open innovation can be extremely beneficial but relies critically on the quality of its inputs. In this case, quality refers to a large enough volume of diverse individuals’ data in order to improve the accuracy and relevance of the research.

I think your suggestion of integrating the various ‘smart’ devices into a single platform is a critical component of the answer to your question regarding appealing to the mass market. With so many devices that require different apps, chargers, etc. it is easy for consumers to feel overwhelmed by this market. By allowing consumers to control their ‘smart home’ all in one app, I think Nest is much more likely to see higher adoption rates.

Pocahontas, you raise two issues that have both crossed my mind as a moderate Waze user. I am glad to hear that the company is taking steps to address the first issue of driver reporting. Using voice recognition seems like a logical solution and Waze could leverage machine learning to create the voice recognition solution.

As for the second issue, I agree that outsmarting speed traps is viewed by its users as a key advantage for the Waze app over Google or Apple maps. Given that crowdsourcing is so integral to Waze’s value proposition, I don’t envision Waze eliminating this feature as, like you suggest, they risk alienating their loyal user base. I wonder if they could instead start incentivizing safe driving through its point system. I’m not sure if that would provide enough incentive to change consumer behavior but it could be worth exploring.

Dook, your point about Walmart’s physical presence being an advantage over Amazon is an interesting one. In my own experience, I feel pretty brand loyal to Target and thus often buy both in store and online from Target, when I could easily purchase the same or similar products from Amazon.

To address one of your questions, I think that ML does have a place in customer service. However, I agree with the customers you cite above that chatbots are not the right area. Personally, whenever I am confronted with a chatbot, I find their answers to be too generic and get frustrated with the lack of personalized service and attention. Instead of chatbots, I think firms should use ML to improve their ability to detect, predict, mitigate, and/or resolve common customer issues and pair that with human contact.