Very interesting article. The competition between automakers is fierce when it comes to self-driving cars so some question came to my mind while I was reading your article:
– What is Toyota value added compare to some other concept cars providing similar services? (example, “Rinspeed” https://youtu.be/6sP-0bIxR6U)
– While the concept is interesting, it seems to particularly be effective in connected cities. This last point has been a barrier for many automakers so far as the initial investment and regulations have been huge barriers to entry. Toyota wants to use Tokyo Olympic/Paralympic in 2020 but do you think the concept is viable?
– When do you think such concept cars will invade our streets and what main steps need to be taken to ensure safety and adoption by customers?
Very interesting article and topic. I love the idea of customizing shoes’ soles to improve the overall shoe design and maybe solve discomfort issues for everyday’s users and not only athletes.
However, I wonder how the profitability after 100k pairs of shoes sold compares to more “classical” production methods.
Also if successful, I have trouble to see what could be a barrier to entry for Adidas main competitor, Nike. The technology has been here for quite some time and has been grabbing attention from industrial manufacturers. Do you believe the company really plan to build on this production method or instead is trying to deploy a marketing campaign?
Very interesting article. The application of ML and AI in data centers to reduce energy consumption seems effective as Google proved it. How would you advise Vertiv to differentiate and protect itself from competitors? As you said yourself, Google already implemented this technology successfully and it seems that nothing prevents the company from selling the “technology/knowledge” to key customers.
This is a very interesting article. France was trying to develop a similar idea by attracting talents / promoting open innovation with mediocre success. Do you think Skolkovo concept could have been successful and if so, how would fix the situation? Is the corrupted government the only factor that prevented success?
Very interesting article and project. A few questions came to my mind while reading your article description:
– From the first screenshot, it seems Marlo will be fed with emails from HBS email address. Can many emails addresses be linked to the same user/calendar and to which extent can the model learn to adapt based on sender/receiver (email address specifics)/ content/time etc..?
– Individual preferences can change widely with time (student “transformative experience” & expectation RC/EC year for example). How can the model be revised partially? Can a user define her “current mood” or some other kind of targets to influence the ML?
– What barriers to entry do you think exist to prevent copycats?
Very interesting article! I wish the students were given a bit more room to write about the topics selected. It could be useful to spend a bit more time explaining the main challenges between LTL and TL for example. A few questions that came to my mind while reading your article :
– What is the impact of companies such as Uber on the fragmented trucking industry? (https://www.uberfreight.com/)
– Can we foresee, before deployment of AI and ML, other solutions being considered to improve the situation? (mom-and-pop shops consolidation into a third party player/intermediary to consolidate shipments and set prices?)