adventurezone

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On November 13, 2018, adventurezone commented on Using Machine Learning to Combat Deforestation :

I think the role of distributed innovation is high here. This appears to be a robust and unique data set. One topic that comes immediately to mind is the role of this data set in noise pollution research. Can this dataset be leveraged by citizens of the community to assess human noise and its impact on animals in an area? I hope so!

On November 13, 2018, adventurezone commented on StoryCorps: Crowdsourcing to Preserve Humanity’s Stories :

I think StoryCorps has the potential to reengage its storytellers and encourage them to create story arcs of their family or their lives. As individuals become power users, it will not only increase the skills of each interviewer creating more quality stories, but it will also create buzz and spread the word about the organization. win-win!!

On November 13, 2018, adventurezone commented on Partnering with AI: Optum Labs’ Efforts to Improve U.S. Health Care :

While I do think that Optum has a responsibility to act ethically (as I believe all companies do) I think it is possible to frame their product as a decision augmentation tool for doctors, which would simply provide them with more data, as a recommendation. It would be still up to professionals what the appropriate course of action (in the case of a diagnosed disease) or diagnosis (in the case of symptoms or pain in a patient).

I completely agree. I also think that an opportunity for Proven will be to address the different skin types on a person’s face (dry cheeks and an oily forehead), which could be the source of customer satisfaction. Likely this will come from a more granular analysis of data which could be difficult for Proven to obtain.

On November 13, 2018, adventurezone commented on From Idea to 3-D in a Day: UPS and Fast Radius :

Initially, I thought a solution to the scaling problem could be the sharing of prototypes or basic models to streamline the production. Upon further reflection, it could pose some challenges with respect to proprietary knowledge, since firms are using them for rapid prototyping, which is likely confidential as a part of product development. That being said, its might be possible to gain more market traction by making the process easier or appealing to the masses in an accessible way. It sure would be nice to be able to replace the chess piece I lost.

On November 13, 2018, adventurezone commented on Crafting a Tailor-Made Bone – Leveraging 3D Printing in Healthcare :

This technology seems like it could substantially change trauma surgeries as we know it, across the globe. A few ideas for how to scale include starting with a generic model, using similar past constructions as a starting point, having simpler bones designed by newer folks. Additionally, it seems that Meticuly has a strong value proposition and is in the position to change the lives of many, across Thailand and the globe. In order to scale the company should secure additional funding and try to partner with larger hospital systems. Ideally this would enable an exchange of ideas between top surgeons (product users) and would enable word of mouth marketing to other hospitals and regions.

On November 9, 2018, ovonnieda commented on Visual Deep Learning – The Power of Images at Pinterest :

In a world where we commercialize data all the time, I think selling its data would be a significant revenue generator for Pintrest. That being said, I have some ethical qualms with the selling of consumer data, particularly without the express permission of the consumer.

I do not think this is a sustainable approach to innovation. I am underwhelmed by the process of skydiving VR (isn’t the point of skydiving to feel the rush of pure adrenaline and have some risk in your life?!?).

On November 9, 2018, ovonnieda commented on Amazon Go: The Future of Grocery Stores :

Yes, I think is this technology was available at scale it would transform almost every buying experience of physical items. Much the way amazon disrupted the way we purchase items, this is just another instance of them creating convenience for a slightly different buying experience and will further entrench themselves into the lives of 21st century daily habits.

I think it is paramount that Lily be aware of the ethical issues of providing accurate and safe information. In the developing world, (but I also believe this to be true worldwide), we need to hold companies to extremely high ethical bars as to not take advantage of , disenfranchise or do harm to those who have been historically underserved and ignored by society.

On November 9, 2018, ovonnieda commented on Stitch Fix: The Fashion Maven of Machine Learning :

I think Stitch Fix is competitively situated well against Amazon because of the human element to their process, at least in the short term. I agree there might be a future where AI is on the same level with human pattern recognition, but I don’t think we are there yet. Therefore, Stitch Fix’s stylists continue to provide “that special something”, that Amazon does not have.

On November 9, 2018, ovonnieda commented on Hinge and Machine Learning: The makings of a perfect match :

To address your first question, I think that Hinge should be worried about competitors adapting its technology. Dating companies benefit significantly from the network effect, so Tinder has a definitive competitive edge. There seem to be low barriers from Tinder using its platform and user base to replicate Hinge’s competitive edge.