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On November 15, 2018, CanadianX commented on John Deere: From Equipment Manufacturer to AgTech Firm :

Thanks for this Jane Deere! Its really exciting to see a 180-year old company reinventing itself to match the technology of the current day and age. I think the M&A approach John Deere leveraged to acquire Blue Mountain’s technology was a smart way to get around the difficulty they have attracting tech talent as a non-traditional technology firm. I’m curious on the quality of the data that exists in the agriculture industry (which is critical for machine learning) and whether John Deere, as a large established firm, could play a role in improving data collection.

On November 15, 2018, CanadianX commented on San José Tackles Open Innovation for Smart Cities :

Thank you for this interesting article Nancy! I think its great that San José is using open innovation as a means to get around the lack of expertise in “smart city” technology that exists in a more traditional government enterprise. There are other cities working to develop “smart cities” – for example, Sidewalk Labs (part of Google) is designing a Smart City in a section of Toronto ( I am curious if the cities tackling this challenge could work together to create something greater than each city could develop on its own – would this contradict San José’s goal to be the most innovative city?

On November 15, 2018, CanadianX commented on Glossier Beauty: Innovating, Not Inundating :

Thanks for your article JStudent! The concept of alienating consumers who put time / effort into their comments and don’t see them turn into a product seems like a very real risk Glossier must monitor closely. Additionally, I wonder how time intensive this open innovation process is for the Glossier team: do they have to read every comment and draw themes manually? Having recently explored machine learning, I would curious if it could be used here to more quickly and effectively draw insights from all the information Glossier is receiving from its customers.

On November 15, 2018, CanadianX commented on Additive Manufacturing at GE Aviation :

Thank you for this Carlos. I’m not sure how I would feel about flying in a plane that was 3D printed, but it seems like this could be the way of the future! I was interested that you suggested moving away from M&A; to do this GE would have to believe they have the right engineering talent in house (or can attract it) and processes in place that allow for the development of this revolutionary additive manufacturing technology. I suspect they will need to take a hard look at themselves before moving forward with this approach. I would also be interested in how additive manufacturing can be used across GE’s other lines of business, and whether it makes sense to set up a central group focused on driving rapid technology development, then applying it to different functional groups (including GE Aviation).

Thank you Justin – this article was very enlightening on a topic I wasn’t familiar with! I like that you highlighted M&A as a strategy that large, established construction firms could use to build these capabilities. This approach seems much more practical that building R&D in-house, given how difficult it would be to attract the right engineering talent for construction firms that aren’t generally thought of as “innovators.” I would be interested to further explore the social good that could come from this lower cost, faster to produce housing – it sounds like this has the potential to reduce homelessness, particularly in developing regions and cities with out of control housing markets.

Great work Sam! I wrote on this topic from the the perspective of a Canadian grocery store who will soon be competing with Amazon’s grocery business. Amazon’s accomplishment with Amazon Go certainly makes them more intimidating for current and future competitors. On your recommendations for reducing CAPEX and experimenting with store designs, I am curious if there are ways for Amazon to leverage its machine learning capabilities to accomplish this. The applications for machine learning seem like they have potential to be applied more broadly across all aspects of business.