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On November 15, 2018, gcakil@mba2020.hbs.edu commented on Snowy Cheese Flavored Latte: Starbucks and Machine Learning in China :

Great read Mutian, thank you so much! Similar to my article, one of the biggest issues to tackle with machine learning are the more personal stuff such as taste. In order to identify what a customer would like as taste, you would need to identify some attributes (ideally many) to somewhat indicate the flavors. These personal attributes (other than basic demographic ones) might be difficult for starbucks to access and analyze.

Great read thank you!

I am very excited about the opportunities for ML in healthcare, and this is indeed one of the burning areas. I see that your proposition would work like this: based on past data and patient outcomes, AI will suggest set of actions. Building this is ofcourse not trivial, however I see some more barriers than that. While building the AI, you would need tremendous amount of phsycian input. Ideally, they also need to understand machine learning concepts. Getting these people on board for a long time might be very costly, and they also might not want it since it shrinks their industry.

On November 15, 2018, gcakil@mba2020.hbs.edu commented on It’s Only A Matter Of Time: ML Sets Its Sights On Your Calendar :

Amazing topic, thank you so much! I am personally very excited about this, and I dream about having an AI assistant to not just manage my calendar but be actually much more than that. But calendar is a great start. Whenever I try to switch to a different calendar, integration with existing calendars has been the most painful issue. Most companies fail to solve this seamlessly for the user. Moreover, since there are tech giants also working on similar solutions, they might also make it much more difficult to integrate it with their systems.

On November 15, 2018, gcakil@mba2020.hbs.edu commented on Additive manufacturing – Will the world’s next mega city drop out of a 3D printer? :

Interesting read Adebodun, thank you! When I read your post, my first concern would be the required skills needed and how they would be developed. I see that you also mentioned this as potential challenges. Developing the skills is one aspect, but as the result of the automation of many things, I have a bigger concern of unemployment. When we think about the construction industry and how many jobs that it creates, it might be catastrophic to disrupt this industry. This is not only the result of additive manufacturing, but also many technological developments.

On November 15, 2018, gcakil@mba2020.hbs.edu commented on The AI Doctor will see you now – Machine learning transforming healthcare :

Very good read, thank you so much! Having worked in primary care services as a consultant, I truly believe in the value of preventive and primary care and I also am a very strong supporter of the use of technology. I have personally seen two main challenges with this: healthcare professionals are very proud of their occupation, and most do not believe that technology could add value to their diagnosis and treatment. So I see this group as a “difficult to create buy-in”. Another potential challenge would be the accountability and ethical aspects of this. Similar to the discussions with autonomous cars, when there is malpractice, who would we blame?