hb178

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While DHL has traditional done business by examining historical data, it is now using machine learning to deliver packages in a quicker, less expensive manner. As we learned today in LEAD, the key to success is to be able to look around the corner and prepare for what is coming next. It sounds like that is exactly what DHL is doing when it comes to its steps towards fully autonomous operations. I think a key to DHL’s future success will be to communicate these advantages to its customers. I am sure that others in the field, such as UPS and FedEx are exploring similar technologies. If DHL wants to remain a leader in the industry, it should be transparent with customers about all they have to gain from using the DHL service.

It is inspiring to hear that machine learning technology is being applied to a governmental agency. I think the public-private partnership is ideal because it helps bring innovation to a sector that is traditionally lacking in resources. I think companies should be transparent when discussing the ways in which the technology is applied even if they aren’t sharing the details of the technology’s inner workings. I am curious if this same framework could be applied to similar government agencies in cities across Pennsylvania and across the country. How easy is it to integrate machine learning into existing databases while protecting the integrity and privacy of the data?

On November 15, 2018, hb178 commented on Crowdsourcing at Amazon: Democratization of TV / Film Content :

What an interesting read! It sounds like crowd sourcing at later stages of the development process is more costly because of the time/delays associated with it. If Amazon were to reignite this program, I would recommend focuses on idea generation. One huge huge trend in television right now is hearing from traditionally under represented voices (Transparent, Fresh Off the Boat, Blackish, etc.). I wonder if there is an opportunity for audiences to play a role by voting on what topics they want to see on screen in terms of race, gender, socio-economic status, international stories, family dynamics, etc. I would encourage Amazon to engage with audiences in this very early stage to help the company identify gaps in their story telling coverage.

On November 15, 2018, hb178 commented on Crowdsourcing at Amazon: Democratization of TV / Film Content :

What an interested read! It sounds like crowd sourcing at later stages of the development process is more costly because of the time/delays associated with it. If Amazon were to reignite this program, I would recommend focuses on idea generation. One huge huge trend in television right now is hearing from traditionally under represented voices (Transparent, Fresh Off the Boat, Blackish, etc.). I wonder if there is an opportunity for audiences to play a role by voting on what topics they want to see on screen in terms of race, gender, socio-economic status, international stories, family dynamics, etc. I would encourage Amazon to engage with audiences in this very early stage to help the company identify gaps in their story telling coverage.

I completely understand the value of targeting advertising. As you said, “This improves consumers’ experience with advertising because they are targeted with content that is more relevant to them, leading to higher click rates.” However, you mentioned the question of consumer privacy and I similarly wonder if this new “responsive search” technology will hit a threshold of efficacy. Customer know when a brand is stalking them. Does this constant and/or hyper-personalized presence help close the sale or does it negatively impact the customer’s perception of the brand? I wonder if more research can be done to understand where that line resides. Are there lessons to be learned from traditional advertising – when does a brand become known for its ubiquitous advertising instead of as a brand? Is all news/presence good news? Thanks for an interesting read!

I appreciate that you took on such an interesting angel within the additive manufacturing space. I am very curious to see where Lumiena is headed next.

The main context in which I have seen 3D printers succeed is when a company is experimenting with either a tool or product that are looking to mass produce. The 3D printer allows a company to play with shapes, flexibility, the amount of material needed. But as you mentioned, what material you use in the 3D printer is key and I am concerned that Lumiena will be able to find a material that can withstand wear and tear in the long run. I understand why Lumiena has pursued 3D printing thus far, but what are they biggest hesitations for outsourcing production at this point in time? Are there stillno manufacturing who could produce what they need? Is it a question of cost? I don’t see how they will be able to resolve this bottleneck issue without overhauling their manufacturing process completely.

How interesting! I did not know that the beauty sector has grown in both online and offline channels while B&M sales in other retail sectors have declined (with the growth of online sales). From this article, I learned that L’Oréal’s main approach has been to connect with entrepreneurs at the cutting edge of their industry. Rather than source ideas from the public, L’Oréal is partnering with thought leaders who are similarly experimenting at the intersection of beauty and technology. I was struck by your comment “L’Oréal’s open innovation program is more attuned to discovering the future of beauty than iterating the present.”
While you question their resistance to engage in open innovation efforts with consumers, I believe it is precisely because they do not want to make their R&D efforts “public domain,” just as you said. By working closely with small companies, they have positioned themselves to gain significant insights from industry innovators and not waste time qualifying valuable consumer ideas.