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Anonymous_HBS_Student
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Really interesting article about a bold experiment on open innovation in the entertainment space!
My question is: how well does completely open sourcing really work in entertainment? TV/Film writing is notorious for having extremely low talent density (few very talented individuals among a huge number of individuals trying to participate in the space). Should Amazon be seeking contributions / submissions from only qualified individuals? Or should they continue accepting submissions from literally anyone?
Really interesting – and shockingly technical – overview of additive manufacturing / 3D printing in the aerospace sector.
Questions that come to mind are: A) is there something specific about military-facing companies that make additive manufacturing particularly attractive (e.g., subsidized R&D budgets, higher demand for advanced tech) or does the same opportunity exist for all aerospace firms? B) Assuming that these technologies represent competitive advantages, that there are sufficient end-users willing to pay for the technology, and that new technology is patentable, why wouldn’t Bell continue to invest in developing technologies?
Great overview of opportunities in the internet of things space and the value that open innovation can bring!
How would you structure a “20% free time” structure for employees? Specifically, how do you motivate employees to produce projects / products that will be impactful for the business, especially if there isn’t an existing culture of doing so? Also, is there any way of expanding this type of structure outside of your own employee base (therefore increasing the openness of open innovation)?
Interesting take on the current uses and opportunities of Machine Learning in the video game space.
I don’t think I understand the conflict outlined in your closing paragraph. How have companies been using ML to drive increased microtransactions? Why do you think this carries reputational risk? Many e-commerce businesses use ML to drive incremental purchasing / revenue (e.g., Amazon), and consumers accept it as normal course. Why are video games different?
This is a very well written and informative overview of Spotify’s approach to machine learning, especially the challenge / current (partial) solution to the Cold Start problem. Thank you!!
Regarding the issue of gender imbalances – if I was a manager at Spotify, I would be concerned that “artificially” increasing gender representation to proportions not represented in the supply of musicians has the potential to decrease customer satisfaction. I would think that increasing gender diversity at the top of the funnel would be a more natural way of improving gender diversity and would be more likely to be successful with consumers long-term.