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This was an interesting read. I think the innovation is at the core of this program, also this program has capability of deriving many positive social values. However, I can also foresee some implementation difficulties in addition to what has been mentioned in the article. One example could be finding the right benchmarks to design future goals and aspirations. This program is unique and hence some out-of-box thinking would be required to push it in the right direction.

On November 15, 2018, Ashima_Singh commented on Great Scott! What’s next for open innovation at LEGO? :

It was great reading this article. I believe for Lego to stay ‘alive and relevant’ in today’s virtual world it is extremely important to shift to open innovation. If Lego let’s it’s customers design products in addition to it’s current offerings, it will skyrocket the growth. Additionally, identifying right customer group and pushing targeted crowdsourcing will also give them more precise vision.

On November 15, 2018, Ashima_Singh commented on Innovation through acquisition at General Mills :

I like the new idea that you have brought as part of this article. However, I believe given General Mills is a big conglomerate that has invested heavily in their R&D for tens of years – both in terms of human resources and machinery etc, it makes little sense to outsource innovation now. I think we can utilize the combination of internal and external resources – but complete shift would not be very productive for the company.

This is a very well written article, highlighting both sides of the story. My only concern with this approach of 3D printing is gaining scale over time. You have mentioned that 3D printing will become a household name in near future, but I am a bit skeptical about this growth especially because of cost and awareness of benefits. Also, in my past experience I worked in geotextiles where 3D printing work started ages ago, but has not been able to scale so far.

On November 15, 2018, Ashima_Singh commented on Machine learning to save millions of dollars of advertising waste at P&G :

It is a great article. Ad fraud is one of the emerging topics in marketing across most industries. One of the outstanding questions of that, however, is that given the insufficiency of data in this field – is it possible to scale this mechanism using machine learning tactics, especially if we think broadly about other industries .Given machine learning solely depends on data, is there a way out of it given this is a great idea?

I think this is a very well written article. Cambridge Analytica case brought together quite a few important topics in consideration of society such as privacy/ ethical grounds regarding usage of virtual data, political advertising etc. As mentioned in the article, we have to be very cautious in design/ model Machine learning tools as it is difficult to teach machine what is right/wrong unless a human teaches it what is right/wrong. Election is an emotional phenomena for many people around the world and hence teaching the machine right thing to do is very critical.