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On November 15, 2018, Covfefe commented on Dementia Discovery Fund: Crowdsourcing a Cure for Alzheimer’s :

As has been said before, very nice article. I’m curious the extent to which picking “winners” to invest in impacts the potential benefits of open innovation as there may be ideas passed over which could have been the breakthroughs, though the bar for investment may be low if primarily funded by charity. I’m also curious about the extent to which they are beholden to external LPs. If they are responsible to external LPs, I could see downside potential in pressure to over-curate investment choices limiting the benefits of open innovation, as well as the benefit of being able to stick to the high risk non-diversified strategy focused on dimension as the external LPs will be theoretically highly diversified investors already. If primarily beholden to internal stakeholders or charity stakeholders, I could see the incentives reversing toward broader investment opportunities but requiring greater diversification to lower the stand-alone risk of the firm. It will be interesting to see how they navigate the capital pressures in striving to maintain as open an approach as possible to maximize the potential for finding solutions.

On November 15, 2018, Covfefe commented on StoryCorps: Crowdsourcing to Preserve Humanity’s Stories :

I was thrilled to see that StoryCorps not only has a podcast to share its message, but that the podcast has over 500 episodes! I agree with SatoshiK’s question regarding the insights that can be drawn from these recordings, but with proper curation I do believe these authentic, approachable, and real stories can be quite powerful in opening up people’s eyes to parts of the human experience that they might not otherwise have been exposed to. Even without true insights, this outcome is a very positive one.

On November 14, 2018, Covfefe commented on From Idea to 3-D in a Day: UPS and Fast Radius :

Mike – thank you for this thoughtful article. Like Yury, I see significant similarities with Amazon. In terms of market potential, I currently see two potential paths forward for this partnership to achieve growth. First, there may be a market opportunity to manufacture at “scale” highly complex and customized products which are uniquely suited to the advantages of 3D printing. Second, there may be value in serving as a highly flexible overflow manufacturing facility, 3D printing products at slower speeds than a client’s factory during times when the client’s factory cannot meet all of the demand. It will be interesting to see how they end up developing their offering and if 3D printing is able to scale sufficiently to move out of the prototyping niche.

ST – thank you for writing about such an interesting topic! I was completely unaware of 3D printing in the construction space, and this has raised so many questions in my mind as to how it would be implemented and what scale is achievable. Is 3D printing in construction primarily applicable to developing economies with less complex construction needs (piping, electronics)? What types of materials can be used in the 3D printing and is it flexible enough to work in all climates (rainy vs wet, hot vs cold)? Would this be more helpful in urban environments due to the current need for shipping the pre-assembly pieces, or more helpful in rural environments where construction materials and talent are in shorter supply? I look forward to watching this early-stage industry develop and find answers to these questions!

On November 14, 2018, Covfefe commented on Turning Big Data into Clean Electrons at NextEra :

It’s great to see cost reduction and operational improvement in solar and wind beyond direct asset innovation. While improved material science enabling larger wind turbines is great, the extra improvement machine learning and other technologies offer provide compounding benefits which accelerate the trend toward renewables you discuss in the beginning of your article. It will be interesting to follow NextEra’s use of machine learning to see where else they apply it in the coming years as they strive to stay ahead of the competition.

On November 14, 2018, Covfefe commented on Driving the Growth of Solar Energy Through Machine Learning :

Trevor – very interesting article. I found it interesting to learn how much opportunity there is to better forecast solar degradation and how variable degradation rates across panels are likely unknown and driving hidden performance gaps long-term. My initial reaction to the pursuit of solar irradiance forecasting is that it requires a completely different set of skills, data, and algorithms to solve which poses a massive barrier; however, I see their insurance products being their core business model long-term and cracking the solar irradiance forecasting would likely help them offer a broader and more robust suite of insurance products. Will be interesting to watch them in the coming years!