In response to your second question, I think Winsun should focus on its core competency of constructing buildings instead of entering the other markets, because first, the global construction market is so huge, but the dominating technology is still very traditional. Even just focusing on this market could bring Winsun massive opportunities. Second, similar to application in construction market, applying 3D printing to other traditional industries requires a lot of efforts in educating key stakeholders and large amount of investment in the technology with high uncertainty. Despite the leading position in construction, Winsun might not be well-positioned for these challenges at the current stage.
To answer your question, I think when machine and human reach to different conclusions, it’s important to understand where the difference comes from, similar to understand why Watson asks the question “what is Toronto” in Jeopardy -for example does it come from the machine putting too much weight on former investors, etc. But I assume the challenge would be it’s difficult to answer that question in most cases. Another potential concern of machine learning-based investment decision is how can machine quantify certain unquantifiable but important aspects, such as the determination and execution capability of the founding team. Maybe this is another area where the human can provide input based on their interview with the founders, etc.
Interesting topic! I am overall skeptical about whether machine learning can find me my song list, because according to what you say, it predicts my tastes by analyzing my past listening behavior, such as the using NLP to analyze lyrics or finding an user with similar tastes to me. But I think personal tastes evolve with time – I want to hear something totally different today than I did yesterday, because each moment I am in different mood. Unless machine learning can read my mind and uncover the tiny emotions that I myself can not describe accurately, I don’t think it can craft a perfect song list for me.
If I were a researcher, I would be very skeptical about the research results published by 23andMe, because it’s solely dependent on the self-reports of customers, which can be biased and full of error even with the best intention of customers. The fact that the research based on these unreliable inputs is used for other customers to reference on efficacy of treatments is even more disturbing – what if you are conveying a wrong message, discouraging patients to seek proper treatment? One potential way to mitigate this risk is perhaps by working with hospitals and cross-checking the self-reported information, or give more detailed instructions/templates to customers for reporting purpose, which would increase the burden of customers and make the product less attractive. Overall I definitely see a trade-off between accuracy and efficiency.
Like the topic very much! (especially after today’s Nike case) . I definitely see your point that Nike should free up resources to broaden up the applications of additive manufacturing to stay ahead in the competition, but it is important that they ensure a proper quality standard before rolling out the application. As a sport brand, Nike have been trying hard to maintain their brand equity of superior performance, for example partnering with world class athletes. If they want to expand into tennis rackets, soccer balls and golf clubs, they should rather do it slowly than jeopardize the product quality and the image of high performance and professional sport brand.
To answer your question, I believe it makes sense for Unilever to identify promising brands early on and it’s actually not too far away from their core strengths – they already have Unilever Ventures which I believe is the venture capital investment arm of the company, and they have profound product marketing knowledge and geographical expertise within specific market to make reasonable investment decisions. Another source of innovation I can think of is internal / customer product innovation, with product innovation ideas coming from employees and customers – I believe 3M is a leader in that area. Given Unilever’s proximity to customers, this can be another potential area for them to look into.